Method and kit for characterizing microorganisms

ABSTRACT

The present disclosure provides methods of characterizing one or more microorganisms and kits for characterizing at least one microorganism. Exemplary methods include preparing an amplicon library, sequencing a characteristic gene sequence to obtain a gene sequence, and characterizing the one or more microorganisms based on the gene sequence using a computer-based genomic analysis of the gene sequence. Exemplary kits include at least one forward primer including an adapter sequence and a priming sequence, for a target sequence, and at least one reverse primer.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of provisional application Ser. No.61/772,425, entitled PAN-BACTERIAL METAGENOMICS ASSAY, and filed Mar. 4,2013, the contents of which are hereby incorporated by reference.

TECHNICAL FIELD

The present disclosure generally relates to methods and kits suitablefor use in the diagnostic field for identification of one or moremicroorganisms.

BACKGROUND

A variety of diagnostic tests are used to assist in the treatment ofpatients with infections. Currently, there are four main modalities totest for the presence of bacterial infections, which are centered on amain diagnostic technology core. These four main modalities are:

1. Microscopy;

2. Serology;

3. Molecular; and

4. Culture.

Each of these modalities has strengths and weaknesses. Microscopy candetect a large number of infections; however, it often lacks specificityto identify which species or even genus to which a particular infectionbelongs. Serology can remotely detect the body's immune response to aninfectious agent; however, this technique assumes the patient isimmuno-competent and only assays a specific bacterium at a time.Molecular diagnostics, typically based on PCR methods, is highlysensitive, but it suffers a similar issue as serology, whereby it onlytests for a specific organism (or sometimes only a specific strain) at atime. Culture methods are unable to detect many strains of organismsthat are currently unculturable.

Many clinical microbiological identification methods rely on passingthrough legacy technologies. One such technology is the culture methodused as a primary enrichment step. Culture depends partially on theassumption that a disease-causing organism is cultivatable.Non-culturable organisms may be entirely missed as an etiologic agentand emerging or unique organisms could easily be misidentified.Molecular identification tests rely upon the amplification of pathogenspecific DNA. These tests are sensitive; however, they usually can onlydetect only a limited number of organisms or genetic variants. Moreover,the starting material for molecular identification typically relies onculture methods. It is fairly well accepted that the majority ofbacteria are present in polymicrobial communities and cannot becultivated.

A number of microbial detection and identification systems have beendeveloped. New protein-based diagnostics such as MALDI TOF massspectroscopy systems are now approved in Europe and are pending approvalin the United States. These systems include the Bruker and bioMerieuxsystems. These systems usually require culture first, rely on a limitedreductionist diagnostic approach, or have a limited throughput.

Blood stream infections (BSIs) are now the most expensive type ofhospital-acquired infection (HAI). A patient's average length ofhospital stay is also affected with sepsis patients staying an averageof about 23.3 days. Furthermore, it is estimated that up to 40% ofpatients receive inadequate initial antibiotic treatment that generatesits complications and considerations. Every hour that appropriateantibiotic treatment is delayed adds to a patient's mortality rate.Delaying appropriate antibiotic treatment by up to 45 hours is anindependent predicting factor for mortality in patients with S. aureusinfections. This is particularly compelling when culture-basedmicroorganism identification and the susceptibility of the identifiedmicroorganism to specific antibiotics often requires between 24 to 72hours.

Rapid microorganism identification would improve patient outcomes.Mortality can be reduced for patients, and even more so with ICUpatients. Length-of-stay reductions could also be realized; studies showthat length of hospital stays could be reduced by 2 days per patient or7 days for an ICU patient with another study showing an overallreduction by 6.2 days per patient. Another study found significant costsavings per patient for pharmacy, laboratory, and bed-related costs whenrapid infection-causing microorganism identification was implemented.

Some rapid diagnostic technologies include advanced MALDI TOF, singleorganism PCR interrogation, and the PCR platform, Biofire.Unfortunately, most of these technologies require preceding culturemethods, in which case, as noted above, uncultivable organisms aremissed. Second, some of these systems have sensitivity andreproducibility issues such as a relatively high error rate in the mostadvanced MALDI TOF systems. Furthermore, these systems can suffer fromsample volume throughput issues whereby single samples or even singlecolony isolates are processed one at a time. Finally, these technologiesusually do not achieve adequate processing turn-around times.

One approach to identify bacteria has been to clone full-length 16S rRNAgenes after polymerase chain reaction (PCR) with primers that wouldamplify genes from a wide range of organisms. Cloned 16S rRNA genes weresequenced by the Sanger method, which requires two or three reads tocover the entire gene. Accuracy is important because sequencing errorscan lead to misclassification. The cost and effort required for theSanger method limits the extent of sampling, and studies often producedabout 100 sequences per sample. This method identifies the dominantmicroorganisms in a sample, but analysis of less abundant microorganismsis limited.

Accordingly: methods and kits are desired that can (1) reliably identifyone or more microorganisms in a time-efficient manner, and/or (2)rapidly sequence multiple regions within microorganism genes (e.g.,hypervariable regions of the genes) to reliably identify one or moremicroorganisms that may be present.

SUMMARY OF THE INVENTION

Various embodiments of the present disclosure relate to methods and kitsthat can be used to characterize or identify one or more microorganisms.In general, various embodiments of the disclosure provide methods andkits that can be used to characterize and/or identify one or moremicroorganisms in a relatively short amount of time. The exemplarymethods and kits can be used to characterize one or more types ofmicroorganisms, such as bacteria, fungi, protozoa, and viruses and/orone or more species of microorganisms within one or more types ofmicroorganisms. Exemplary methods and systems can evaluate a pluralityof microorganisms at the same time, in parallel, to further reduce theamount of time associated with identification or characterization ofmultiple microorganisms. Further, exemplary methods and kits can be usedto characterize or identify one or more microorganisms without requiringa culture step. Because the microorganisms can be characterized oridentified in a short amount of time, exemplary methods and kitsdescribed herein are suitable for clinical applications, where rapididentification of the microorganism(s) is desired. Further, results fromuse of exemplary systems and kits can provide care givers with suggestedtreatments and/or sensitivity and/or therapy resistance informationrelating to various treatments for the characterized or identifiedmicroorganism(s) in a manner that is easy to read and interpret. As usedherein “characterized” or “identified” microorganisms refers to a genusor a species of the characterized or identified microorganism(s) or themicroorganism itself.

In accordance with exemplary embodiments of the disclosure, a method ofcharacterizing one or more microorganisms includes the steps of (a)preparing an amplicon library with a polymerase chain reaction (PCR) ofnucleic acids; (b) sequencing a characteristic gene sequence in theamplicon library to obtain a gene sequence; and (c) characterizing theone or more microorganisms based on the gene sequence using acomputer-based genomic analysis of the gene sequence. In accordance withvarious aspects of these embodiments, the method further includes a stepof extracting nucleic acids from a biological sample of a subject. Inaccordance with additional aspects, the method includes a step ofpurifying the amplicon library from the PCR reaction. As noted above,the microorganisms can include one or more of bacteria, fungi, protozoa,and viruses. In the case of bacteria, a characteristic gene can be 16Sribosomal RNA (16S rRNA). Exemplary techniques for sequencing acharacteristic gene include using an ion semiconductor sequencingplatform or a platform based on stepwise addition of reversibleterminator nucleotides. In accordance with various aspects of theseembodiments, the amplicon library is an ion amplicon library. Variousmethods can be used to identify one or more microorganisms and/or tocharacterize one or more microorganisms or DNA fragments thereof basedon, for example, a nearest known microorganism or DNA fragment thereof.

Exemplary methods of the present disclosure may further comprise thestep of generating a report with microorganisms characterized oridentified and treatment (e.g., antibiotic, antifungal, antiprotozoal,and/or antiviral) resistance and susceptibility information for eachidentified genus and/or species and/or microorganism. The method mayalso further comprise treating the subject with a treatment identifiedin the report.

In certain aspects, the PCR reaction uses a forward primer thatcomprises a target sequence. In the case of bacteria characterization,the target sequence may include a sequence from the 16S rRNA gene suchas a hypervariable region selected from the group consisting of V1, V2,V4, and V5.

In certain implementations, the biological sample is a urine sample, ablood sample, a bronchioalveolar lavage, a nasal swab, cerebrospinalfluid, synovial fluid, brain tissue, cardiac tissue, bone, skin, a lymphnode tissue or a dental tissue. In some embodiments, the dental tissueis a tooth, a soft tissue, a joint sample, or a dental sample.

In another implementation, the computer-based genomic analysis comprisesapplication of a procedural algorithm to sequencing data. The proceduralalgorithm may exclude sequences that are present less than five times orconstitute less than 1% of the sequencing data.

In accordance with additional exemplary embodiments of the disclosure, akit for characterizing at least one microorganism includes (a) at leastone forward primer comprising an adapter sequence and a primingsequence, for a target sequence, wherein the target sequence comprises asequence from a characteristic gene sequence; and (b) at least onereverse primer. If one or more suspected microorganisms includebacteria, the target sequence can be from the 16S rRNA gene and ahypervariable region selected from the group consisting of V1, V2, V4,and V5. In certain aspects, the reverse primer comprises a sequenceselected from the group consisting of SEQ ID NO: 33 and SEQ ID NO: 34.

In some implementations, the kit comprises a first forward primer and asecond forward primer, each of which can include a barcode, a barcodeadapter, and a target sequence. By way of example, a target sequence ofthe first forward primer can include a sequence beginning in V1 andextending towards V2 and the target sequence of the second forwardprimer can include a sequence beginning in V5 and extending towards V4.

Various additional embodiments of the present disclosure relate toelectronic systems and methods that can be used to characterize oridentify one or more microorganisms. For example, a method ofcharacterizing one or more microorganisms includes the step ofselecting, by a computer, a digital file comprising one or more digitalDNA sequences, wherein each of the one or more digital DNA sequencescorresponds to a microorganism to be characterized. The computersegments each of the one or more digital DNA sequences into one or morefirst portions, performs a set of alignments by comparing the one ormore first portions to information stored in a first database,determines sequence portions from among the one or more first portionsthat have an alignment match to the information stored in the firstdatabase, performs a set of alignments by comparing the one or morefirst portions or one or more second portions to information stored in asecond database, determines sequence portions from among the one or morefirst portions or the one or more second portions that have an alignmentmatch to the information stored in the second database, andcharacterizes one or more microorganisms or DNA fragments thereof basedon the alignment match to the information stored in one or more of thefirst database and the second database.

In accordance with various aspects of these embodiments, the method canbe used to characterize multiple microorganisms simultaneously or inparallel, such that multiple microorganisms can be identified in arelatively short amount of time—e.g., preferably in less thanforty-eight or less than twenty-four hours.

In accordance with further exemplary embodiments of the disclosure, anarticle of manufacture including a non-transitory computer readablemedium having instructions stored thereon that, in response to executionby a computing device, cause the computing device to perform operationscomprising the steps described in the above paragraph.

In accordance with additional exemplary embodiments of the disclosure, asystem includes a computer to perform one or more steps, such as themethod steps noted above.

In accordance with further exemplary embodiments of the disclosure, amethod of automatically characterizing one or more microorganisms can beperformed using one or more databases. Exemplary methods include thesteps of detecting a sequence run that generates a digital DNA sequenceof one or more microorganisms; selecting, by a computer, a digital filecomprising one or more digital DNA sequences, wherein each of the one ormore digital DNA sequences corresponds to a microorganism to becharacterized; segmenting, by the computer, each of the one or moredigital DNA sequences into one or more portions; performing, by thecomputer, a set of alignments by comparing the one or more portions toinformation stored in one or more databases; determining, by thecomputer, sequence portions from among the one or more portions thathave an alignment match to the information stored in the one or moredatabases; and characterizing one or more microorganism(s) or DNAfragments thereof based on the alignment match. In accordance withvarious aspects of these embodiments, the method can be used tocharacterize multiple microorganisms simultaneously, such that multiplemicroorganisms can be identified in a relatively short amount oftime—e.g., preferably in less than forty-eight or less than twenty-fourhours.

In accordance with yet additional exemplary embodiments of thedisclosure, an article of manufacture including a non-transitorycomputer readable medium having instructions stored thereon that, inresponse to execution by a computing device, cause the computing deviceto perform operations comprising the steps described in the aboveparagraph.

In accordance with yet additional exemplary embodiments, a system forautomatic computerized generation of microorganism characterizationinformation includes a computer configured to perform the steps of thepreceding paragraph.

BRIEF DESCRIPTION OF THE DRAWINGS

A more complete understanding of exemplary embodiments of the presentdisclosure can be derived by referring to the detailed description andclaims when considered in connection with the following illustrativefigures.

FIG. 1 illustrates bidirectional sequencing using the fusion method. Twoprimer pairs per target region generate two libraries to enablebidirectional sequencing of the target region.

FIG. 2 illustrates fusion PCR primers for bidirectional sequencing.

FIG. 3 illustrates example primers and amplicon design.

FIG. 4 illustrates results of a computer-based genomics analysis of apatient sample with Prevotella spp. as the most abundant microorganismsidentified.

FIG. 5 illustrates results of a computer-based genomics analysis of apatient sample with Capnocytophaga gingivalis as the most abundantmicroorganisms identified.

FIG. 6 presents the results of a computer-based genomics analysis of apatient sample with Actinomyces naeslundii as the most abundantmicroorganisms identified.

FIG. 7A is a graph illustrating the length of sequencing reads versusthe percentage of accurate identifications of the bacterium Ralstoniasolanacearum in a control sample. FIG. 7B is a bar graph illustratingthat as the cutoff for the length of the sequencing reads increases, thenumber of available reads at these higher cutoffs decreases.

FIG. 8 is a bar graph of the cutoff lengths of sequencing reads usingthe V1/2 and V5/4 oligonucleotides plotted against the percentage ofaccurate genus identification with a control sample containing Ralstoniasolanacearum.

FIGS. 9A, 9B, 10A, and 10B depict line graphs demonstrating that aconsistent result is obtained when looking at the two selected 16S rRNAregions of V1/2 and V5/4.

FIG. 11 presents the results of a computer-based genomics analysis of apatient sample with Sphingomonas paucimobilis as the most abundantmicroorganisms identified.

FIG. 12 illustrates a system in accordance with various embodiments ofthe disclosure.

FIG. 13 illustrates a method in accordance with exemplary embodiments ofthe disclosure.

FIG. 14 illustrates a method for automatic sequencing run acquisition inaccordance with further exemplary embodiments of the disclosure.

FIG. 15 illustrates another method in accordance with further exemplaryembodiments of the disclosure.

FIGS. 16-17 illustrate examples of information output in an exemplaryreport generated in accordance with exemplary embodiments of thedisclosure.

FIGS. 18-21 illustrate results of a computer-based genomics analysis isaccordance with further exemplary embodiments of the disclosure.

It will be appreciated that elements in the figures are illustrated forsimplicity and clarity and have not necessarily been drawn to scale. Forexample, the dimensions of some of the elements in the figures may beexaggerated relative to other elements to help to improve theunderstanding of illustrated embodiments of the present disclosure.

DETAILED DESCRIPTION

The description of embodiments provided below is merely exemplary and isintended for purposes of illustration only; the following description isnot intended to limit the scope of the disclosure or the claims.Moreover, recitation of multiple embodiments having stated features isnot intended to exclude other embodiments having additional features orother embodiments incorporating different combinations of the statedfeatures.

The following disclosure provides methods and kits for characterizingone or more microorganisms. Various examples disclosed herein providemethods and kits for characterizing one or more microorganisms or DNAfragments thereof, such as for example, pathogenic microorganisms in anefficient and timely manner, such that the systems and methods aresuitable for use in clinical settings. Exemplary methods and kits canalso provide treatment and/or treatment sensitivity information relatedto the one or more identified microorganism, such that a care providercan use such information. In addition, exemplary methods and kits do notrequire culturing samples.

As used herein, the verb “comprise” as is used in this description andin the claims and its conjugations are used in its non-limiting sense tomean that items following the word are included, but items notspecifically mentioned are not excluded. In addition, reference to anelement by the indefinite article “a” or “an” does not exclude thepossibility that more than one of the elements are present, unless thecontext clearly requires that there is one and only one of the elements.The indefinite article “a” or “an” thus usually means “at least one.”

As used herein, the term “subject” or “patient” refers to any vertebrateincluding, without limitation, humans and other primates (e.g.,chimpanzees and other apes and monkey species), farm animals (e.g.,cattle, sheep, pigs, goats and horses), domestic mammals (e.g., dogs andcats), laboratory animals (e.g., rodents such as mice, rats, and guineapigs), and birds (e.g., domestic, wild and game birds such as chickens,turkeys and other gallinaceous birds, ducks, geese, and the like). Insome embodiments, the subject is a mammal. In other embodiments, thesubject is a human.

As used herein, the term “biological sample” may include but is notlimited to urine, fluid or tissue samples such as blood (e.g., wholeblood, blood serum, etc.), bronchioalveolar lavage, nasal swabs,cerebrospinal fluid, synovial fluid, brain and other neurologicaltissues, cardiac tissue, bone, skin, lymph nodes, dental tissue, and thelike from a subject. The dental tissue may be a tooth, a soft tissue, ordental pulp.

Unless denoted otherwise, whenever a oligonucleotide sequence isrepresented, it will be understood that the nucleotides are in 5′ to 3′order from left to right and that “A” denotes deoxyadenosine, “C”denotes deoxycytidine, “G” denotes deoxyguanosine, “T” denotesthymidine, and “U” denotes deoxyuridine. Oligonucleotides are said tohave “5′ ends” and “3′ ends” because mononucleotides are typicallyreacted to form oligonucleotides via attachment of the 5′ phosphate orequivalent group of one nucleotide to the 3′ hydroxyl or equivalentgroup of its neighboring nucleotide, optionally via a phosphodiester orother suitable linkage. Nucleotides may also be identified as indicatedas shown below in Table 1.

TABLE 1 List of Nucleotide Abbreviations Symbol Meaning Origin ofdesignation A A adenine G G guanine C C cytosine T T thymine U U uracilR G or A purine Y T/U or C pyrimidine M A or C amino K G or T/U keto S Gor C strong interactions 3H-bonds W A or T/U weak interactions 2H-bondsB G or C or T/U not a D A or G or T/U not c H A or C or T/U not g V A orG or C not t, not u N A or G or C or T/U, any unknown, or other

Various embodiments of the present disclosure provide metagenomictesting methods that use direct DNA sequencing and computationalanalysis to enable the detection, characterization or identification,and in the case of novel or divergent organisms the identification ofthe nearest characterized microorganism, microorganism species, and/ormicroorganism genus of multiple organisms at the same time. This standsin stark contrast to the myriad of current indirect testingtechnologies, including serology, T-cell stimulation assays, FISH, andELISA. Furthermore, exemplary methods can provide a relative measure ofthe microorganism contribution and diversity within a given sample. Inthese certain respects, the method may be called Pan-MicrobialMetagenomics as it aims to identify the genetic composition anddiversity across multiple microorganisms in a sample, simultaneously.

Various exemplary methods can characterize, identify, and/or survey theorganisms of an unknown or polymicrobial infection. By using direct DNAsequencing and computational analysis, these methods allow for thecharacterization or identification of the nearest relative to anydetected bacteria in a given clinical sample. Furthermore, the methodsmay also provide a relative measure of the various microbialcontribution and diversity within a given sample in addition topresenting literature based treatment suggestions. Adoption of thedisclosed methods in clinical use will have far reaching implicationsnot only by providing superior, unbiased, sequence based diagnosis, butalso in reducing patient mortality, morbidity, length of stay, andassociated hospital and healthcare costs. In accordance with someexamples, ion semiconductor sequencing platforms or similar techniquesare utilized to carry out the method because they enable an importantaspect of this diagnostic method: speed. In certain aspects, thedisclosed diagnostic method enables a turnaround time for results from apatient sample of about 12 hours, about 24 hours, about 48 hours, orabout 72 hours. This disclosed method may be performed as a LaboratoryDeveloped Test (LDT) in a Clinical Laboratory Improvement Amendments(CLIA) regulated diagnostics laboratory.

In some implementations, the disclosure provides a system consisting ofseven main steps resulting in a CLIA compliant diagnostic billableprocedure. These steps include:

-   -   1. Point of Care Sampling—Infected tissues and/or fluid samples        may be submitted for analysis. Proper collection techniques are        used to minimize contamination of the sample by non-targeted        bacterial populations. Blood draw sites are cleaned thoroughly        with disinfectants to remove bacterial and/or other microbial        DNA and cells, while tissue samples are collected using aseptic        techniques. The disclosed system is supported with industry        standard collection kits if required by the collection facility.    -   2. Rapid Courier Service—Rapid sample transport to the        laboratory is desired to obtain an accurate snapshot of the        microbial communities. Extended transport or storage times may        result in drifts of the bacterial community that could lead to        misleading or distorted results.    -   3. DNA Extraction—Total DNA content is purified appropriately        from a wide range of tissue, fluid, bone and sample types that        are adequate for subsequent processing.    -   4. Molecular Tagging and Amplification—Microbial type specific        DNA fragments are selectively amplified for distinct genomic        regions and tagged with patient specific molecular markers.        These enriched samples of DNA are pooled together in, for        example, equimolar amounts to allow even sequencing results        across patients and between the genomic regions of interest.    -   5. Next-Generation DNA Sequencing—Millions of DNA reads are        produced through the use of semiconductor sequencing. The        sequencing procedure is monitored by a variety of methods to        ensure optimal performance and sequencing coverage for each        sample. The sequences are sorted based on the molecular tags        allowing for consistent and easy identification of the sample        source.    -   6. Bioinformatics Analysis—Software that automatically        interfaces with the sequencing software and analyzes the results        with the selected sequences, chemistry, and methods can be used        with the disclosed methods and system. Such software may utilize        industry standard formats and methods of analysis, thus        providing reliable and result-based methods.    -   7. Results Reporting—The software may output the results into a        variety of formats and automatically backup intermediary work        files documenting the analysis process. Computational metrics        may be presented to the analysis technician for review and final        report building. In addition to bacterial findings, the        disclosed system may provide literature based treatment        recommendations with the associated references.

In accordance with various embodiments of the disclosure, a method ofcharacterizing one or more microorganisms includes the steps ofpreparing an amplicon library with a polymerase chain reaction (PCR) ofnucleic acids; sequencing a characteristic gene sequence in the ampliconlibrary to obtain a gene sequence; and characterizing the one or moremicroorganisms based on the gene sequence using a computer-based genomicanalysis of the gene sequence.

In certain aspects, the present disclosure is directed to a test thatcombines three main components together to provide a unique diagnosticcapability that is currently unavailable in the market and thatspecifically seeks to exploit the exceptional sensitivity of themolecular based assays with a broad spectrum of detection andidentification. The three main components are Sample and LibraryPreparation, DNA Sequencing, and Computer-Based Genomic Analysis.

Accordingly, in one aspect the method of the present disclosurecomprises: Sample and Library Preparation, DNA Sequencing, andComputer-Based Genomic Analysis. In one embodiment, the Sample andLibrary Preparation consists of five steps:

1. DNA Extraction 2. Amplification and Barcoding 3. DNA Purification 4.IonSphere Particle Labeling 5. IonSphere Particle Enrichment

However, each of the five steps is not required to practice allembodiments of the disclosure.

DNA extraction may be accomplished by any method available in the art.Nucleic acids can be extracted from a biological sample by a variety oftechniques such as those described by Maniatis et al., MolecularCloning: A Laboratory Manual, Cold Spring Harbor, N.Y., pp. 280-281,(1982), the contents of which is incorporated by reference herein in itsentirety. In one embodiment, DNA is extracted from the biological samplewith the QIAamp® DNA Mini Kit.

Sample and Library Preparation may also involve the running of apolymerase chain reaction (PCR). PCR is a technique in molecular biologyto amplify a single or few copies of a piece of DNA across severalorders of magnitude, generating thousands to millions of copies of aparticular DNA sequence. The method relies on thermal cycling,consisting of cycles of repeated heating and cooling of the reaction forDNA melting and enzymatic replication of the DNA. Primers (short DNAfragments) containing sequences complementary to the target region alongwith a DNA polymerase (after which the method is named) are componentsto enable selective and repeated amplification. As PCR progresses, theDNA generated is itself used as a template for replication, setting inmotion a chain reaction in which the DNA template is exponentiallyamplified. PCR can be extensively modified to perform a wide array ofgenetic manipulations.

Most PCR applications employ a heat-stable DNA polymerase, such as Taqpolymerase, an enzyme originally isolated from the bacterium Thermusaquaticus. This DNA polymerase enzymatically assembles a new DNA strandfrom DNA building blocks, the nucleotides, by using single-stranded DNAas a template and DNA oligonucleotides (also called DNA primers), whichare used for initiation of DNA synthesis. The vast majority of PCRmethods use thermal cycling, i.e., alternately heating and cooling thePCR sample to a defined series of temperature steps. These thermalcycling steps are necessary first to physically separate the two strandsin a DNA double helix at a high temperature in a process called DNAmelting. At a lower temperature, each strand is then used as thetemplate in DNA synthesis by the DNA polymerase to selectively amplifythe target DNA. The selectivity of PCR results from the use of primersthat are complementary to the DNA region targeted for amplificationunder specific thermal cycling conditions. In one embodiment, thepresent disclosure contemplates a method comprising amplifying aplurality of a complex mixture (“library”) of DNA molecules by PCR.

PCR is used to amplify a specific region of a DNA strand (the DNAtarget) Most PCR methods typically amplify DNA fragments of up to ˜10kilo base pairs (kb), although some techniques allow for amplificationof fragments up to 40 kb in size. A basic PCR set up usually involvesseveral components and reagents. These components may include, but arenot limited to: i) DNA template that contains the DNA region (target) tobe amplified; ii) two primers that are complementary to the 3′ ends ofeach of the sense and anti-sense strand of the DNA target; iii) Taqpolymerase or another DNA polymerase with a temperature optimum ataround 70° C.; iv) deoxynucleoside triphosphates (dNTPs; also verycommonly and erroneously called deoxynucleotide triphosphates), thebuilding blocks from which the DNA polymerases synthesizes a new DNAstrand; v) buffer solution, providing a suitable chemical environmentfor optimum activity and stability of the DNA polymerase; vi) divalentcations, magnesium or manganese ions; generally Mg²⁺ is used, but Mn²⁺can be utilized for PCR-mediated DNA mutagenesis, as higher Mn²⁺concentration may increase the error rate during DNA synthesis; and vii)monovalent cation potassium ions.

The PCR is commonly carried out in a reaction volume of 10-200 μl insmall reaction tubes (0.2-0.5 ml volumes) in a thermal cycler. Thethermal cycler heats and cools the reaction tubes to achieve thetemperatures at each step of the reaction. Many modern thermal cyclersmake use of the Peltier effect which permits both heating and cooling ofthe block holding the PCR tubes simply by reversing the electriccurrent. Thin-walled reaction tubes permit favorable thermalconductivity to allow for rapid thermal equilibration. Most thermalcyclers have heated lids to prevent condensation at the top of thereaction tube, but a layer of oil or a ball of wax may also beeffective.

In some embodiments, the method of the present disclosure comprisespreparing an ion amplicon library. This may be accomplished with thefusion PCR method using fusion primers to attach the Ion A and truncatedP1 (trP1) Adapters to the amplicons as they are generated in PCR (seeFIG. 1). The fusion primers contain the A and trP1 sequences at their5′-ends adjacent to the target-specific portions of the primers (seeFIG. 2). The target region is the portion of the genome that will besequenced in the samples of interest. For example the target regioncould be an exon, a portion of an exon, or a non-coding region of thegenome. Primers are designed so that any sequence variants of interestare located between the primers and so those variants are not masked bythe template-specific part of the primer sequences (see FIG. 3). Thelength of the target region is also carefully considered. In oneexample, bidirectional sequencing is used. In another example,sequencing proceeds in a single direction.

For bidirectional sequencing, the fusion PCR method for preparing anamplicon library generally uses four fusion primers: two pairs offorward and reverse primers per target region. If sequencing proceeds ina single direction, only one pair of forward and reverse primers pertarget may be used. The amplicons are designed so that their length,including the fusion primers with adapter sequences, is shorter than themedian library size for the target read length of the library (see Table2).

TABLE 2 Design of Amplicon Length Target Read Length Median Library Size200 bases (200 base-read library) ~330 bp 100 bases (100 base-readlibrary) ~200 bp

One fusion primer pair has the A adapter region followed by the proximalend of the target sequence, and the other has the trP1 adapter regionfollowed by the distal end of the target sequence. The other fusionprimer pair has the adapter sequences A and trP1 swapped. Thetarget-specific portion of each primer should include 15-20 nucleotidesof the target region.

In some embodiments, the fusion primer contains a “barcode.” The term“barcode” as used herein, refers to any unique, non-naturally occurring,nucleic acid sequence that may be used to identify the originatinggenome of a nucleic acid fragment. Such barcodes may be sequencesincluding but not limited to: CTAAGGTAAC (SEQ ID NO: 1), TAAGGAGAAC (SEQID NO: 2), AAGAGGATTC (SEQ ID NO: 3), TACCAAGATC (SEQ ID NO: 4),CAGAAGGAAC (SEQ ID NO: 5), CTGCAAGTTC (SEQ ID NO: 6), TTCGTGATTC (SEQ IDNO: 7), TTCCGATAAC (SEQ ID NO: 8), TGAGCGGAAC (SEQ ID NO: 9), CTGACCGAAC(SEQ ID NO: 10), TCCTCGAATC (SEQ ID NO: 11), TAGGTGGTTC (SEQ ID NO: 12),TCTAACGGAC (SEQ ID NO: 13), TTGGAGTGTC (SEQ ID NO: 14), TCTAGAGGTC (SEQID NO: 15), or TCTGGATGAC (SEQ ID NO: 16). Barcodes may, optionally, befollowed by a barcode adapter, for example, GAT (SEQ ID NO: 17). Whileexemplary barcodes are listed, any barcode of an appropriate lengthcontaining an arbitrary DNA sequence may be used with the method of thepresent disclosure. An appropriate length for the barcode may be about 5nucleotides, about 6 nucleotides, about 7 nucleotides, about 8nucleotides, about 9 nucleotides, about 10 nucleotides, about 15nucleotides or about 20 nucleotides.

In accordance with various aspects of the present disclosure, the targetsequence is a segment from the 16S rRNA gene of a microorganism. In someimplementations, the target sequence may comprise one or morehypervariable regions from the 16S rRNA gene selected from V1, V2, V3,V4, V5, V6, V7, V8, and V9. For example, the target sequence comprises asequence from any one of V1, V2, V4, and V5. In another implementation,the target sequence may comprise a sequence beginning in V1 andextending towards V2, a sequence beginning in V2 and extending towardsV1, a sequence beginning in V4 and extending towards V5, or a sequencebeginning in V5 and extending towards V4. The target sequence may beanywhere from about 5 nucleotides in length to about 40 nucleotides inlength, from about 10 nucleotides in length to about 30 nucleotides inlength, from about 15 nucleotides in length to about 25 nucleotides inlength, etc. In some implementations, the target sequence is about 5nucleotides in length, about 10 nucleotides in length, about 15nucleotides in length, about 20 nucleotides in length, about 25nucleotides in length, about 30 nucleotides in length, about 35nucleotides in length, or about 40 nucleotides in length. Non-limitingexamples of 16S rRNA target sequences that may be used in the fusionprimers are listed in Table 3.

TABLE 3 16S rRNA Target Sequences for Fusion Primers Primer NameSequence (5′-3′) SEQ ID NO: V1/2 AGAGTTTGATCCTGGCTCAG SEQ ID NO: 18 V5/4CCGTCAATTYYTTTRAGTTT SEQ ID NO: 19 U1492R GGTTACCTTGTTACGACTT SEQ ID NO:20 928F TAAAACTYAAAKGAATTGACGGG SEQ ID NO: 21 336RACTGCTGCSYCCCGTAGGAGTCT SEQ ID NO: 22 1100F YAACGAGCGCAACCC SEQ ID NO:23 1100R GGGTTGCGCTCGTTG SEQ ID NO: 24 337F GACTCCTACGGGAGGCWGCAG SEQ IDNO: 25 907R CCGTCAATTCCTTTRAGTTT SEQ ID NO: 26 785F GGATTAGATACCCTGGTASEQ ID NO: 27 805R GACTACCAGGGTATCTAATC SEQ ID NO: 28 533FGTGCCAGCMGCCGCGGTAA SEQ ID NO: 29 518R GTATTACCGCGGCTGCTGG SEQ ID NO: 30

In another aspect of the present disclosure, the target sequence is asegment of an antibiotic resistance gene. Non-limiting examples of suchantibiotic resistance genes include bla_(tem), bla_(shv), bla_(rob),bla_(oxa), blaZ, aadB, aacC1, aacC2, aacC3, aac6′-IIa, aacA4, aad(6′),vanA, vanB, vanC, msrA, sarA, aac(6′) aph(2″), vat, vga, ermA, ermB,ermC, mecA, int, sul, mecA, aac2ia, aac2ib, aac2ic, aac2id, aac2i,aac3ia, aac3iia, aac3iib, aac3iii, aac3iv, aac3ix, aac3vi, aac3viii,aac3vii, aac3x, aac6i, aac6ia, aac6ib, aac6ic, aac6ie, aac6 if, aac6ig,aac6iia, aac6iib, aad9, aad9ib, aadd, acra, acrb, adea, adeb, adec,amra, amrb, ant2ia, ant2ib, ant3ia, ant4iia, ant6ia, aph33ia, aph33ib,aph3ia, aph3ib, aph3ic, aph3iiia, aph3iva, aph3va, aph3vb, aph3via,aph3viia, aph4ib, aph6ia, aph6ib, aph6ic, aph6id, arna, baca, bcra,bcrc, bl1_acc, bl1_ampc, bl1_asba, bl1_ceps, bl1_cmy2, bl1_ec, bl1_fox,bl1_mox, bl1_och, bl1_pao, bl1_pse, bl1_sm, bl2a_(—)1, bl2a_exo,bl2a_iii2, bl2a_iii, bl2a_kcc, bl2a_nps, bl2a_okp, bl2a_pc, bl2be_ctxm,bl2be_oxyl, bl2be_per, bl2be_shv2, bl2b_rob, bl2b_tem1, bl2b_tem2,bl2b_tem, bl2b_tle, bl2b_ula, bl2c_bro, bl2c_pse1, bl2c_pse3, bl2d_lcr1,bl2d_moxa, bl2d_oxa10, bl2d_oxa1, bl2d_oxa2, bl2d_oxa5, bl2d_oxa9,bl2d_r39, bl2e_cbla, bl2e_cepa, bl2e_cfxa, bl2e_fpm, bl2e_y56,bl2f_nmca, bl2f_sme1, bl2_ges, bl2_kpc, bl2_len, bl2_veb, bl3_ccra,bl3_cit, bl3_cpha, bl3_gim, bl3_imp, bl3_(—)1, bl3_shw, bl3_sim,bl3_vim, ble, blt, bmr, cara, cata10, cata11, cata12, cata13, cata14,cata15, cata16, cata1, cata2, cata3, cata4, cata5, cata6, cata7, cata8,cata9, catb1, catb2, catb3, catb4, catb5, ceoa, ceob, cml_e1, cml_e2,cml_e3, cml_e4, cml_e5, cml_e6, cml_e7, cml_e8, dfra10, dfra12, dfra13,dfra14, dfra15, dfra16, dfra17, dfra19, dfra1, dfra20, dfra21, dfra22,dfra23, dfra24, dfra25, dfra25, dfra25, dfra26, dfra5, dfra7, dfrb1,dfrb2, dfrb3, dfrb6, emea, emrd, emre, erea, ereb, erma, ermb, ermc,ermd, erme, ermf, ermg, ermh, ermn, ermo, ermq, ermr, erms, ermt, ermu,ermv, ermw, ermx, ermy, fosa, fosb, fosc, fosx, fusb, fush, ksga, lmra,lmrb, lnua, lnub, lsa, maca, macb, mdte, mdtf, mdtg, mdth, mdtk, mdtl,mdtm, mdtn, mdto, mdtp, meca, mecrl, mefa, mepa, mexa, mexb, mexc, mexd,mexe, mexf, mexh, mexi, mexw, mexx, mexy, mfpa, mpha, mphb, mphc, msra,norm, oleb, opcm, opra, oprd, oprj, oprm, oprn, otra, otrb, pbpla,pbplb, pbp2b, pbp2, pbp2x, pmra, qac, qaca, qacb, qnra, qnrb, qnrs,rosa, rosb, smea, smeb, smec, smed, smee, smef, srmb, sta, str, sul1,sul2, sul3, tcma, tcr3, tet30, tet31, tet32, tet33, tet34, tet36, tet37,tet38, tet39, tet40, teta, tetb, tetc, tetd, tete, tetg, teth, tetj,tetk, tetl, tetm, teto, tetpa, tetpb, tet, tetq, tets, tett, tetu, tetv,tetw, text, tety, tetz, tlrc, tmrb, tolc, tsnr, vana, vanb, vanc, vand,vane, yang, vanha, vanhb, vanhd, vanra, vanrb, vanrc, vanrd, vanre,vanrg, vansa, vansb, vansc, vansd, vanse, vansg, vant, vante, vantg,vanug, vanwb, vanwg, vanxa, vanxb, vanxd, vanxyc, vanxye, vanxyg, vanya,vanyb, vanyd, vanyg, vanz, vata, vatb, vatc, vatd, vate, vgaa, vgab,vgba, vgbb, vph, ykkc, and ykkd (see the Antibiotic Resistance GenesDatabase (ARDB) available online).

When barcodes are incorporated into PCR primers for bidirectionalsequencing, the primers may comprise the following sequences:

Forward Primer #1:

5′-CCATCTCATCCCTGCGTGTCTCCGACTCAG-3′ (SEQ ID NO: 31) followed by abarcode, a barcode adapter, and a stretch of about 20 nucleotides fromthe target sequence;

Reverse Primer #1:

5′-CCATCTCATCCCTGCGTGTCTCCGACTCAG-3′ (SEQ ID NO: 31) followed by abarcode, a barcode adapter, and a stretch of about 20 nucleotides fromthe target sequence;

Forward Primer #2:

5′-CCTCTCTATGGGCAGTCGGTGAT-3′ (SEQ ID NO: 32) followed by a stretch ofabout 20 nucleotides from the target sequence;

Reverse Primer #2:

5′-CCTCTCTATGGGCAGTCGGTGAT-3′ (SEQ ID NO: 32) followed by a stretch ofabout 20 nucleotides from the target sequence.

In some aspects of the present disclosure, sequencing proceeds in onedirection and the reverse primers do not include a barcode sequence or abarcode adapter.

The forward and reverse primers may comprise SEQ ID NO: 31 or SEQ ID NO:32 and a stretch of about 5 nucleotides, about 10 nucleotides, about 15nucleotides, about 20 nucleotides, about 25 nucleotides, or about 30nucleotides from the target sequence.

In certain embodiments, the reverse primer comprises a sequence selectedfrom CCTCTCTATGGGCAGTCGGTGATCTGCTGCCTYCCGTA (SEQ ID NO: 33) andCCTCTCTATGGGCAGTCGGTGATAYTGGGYDTAAAGNG (SEQ ID NO: 34).

In certain embodiments, the method of the present disclosure comprisessequencing 16S ribosomal RNA (16S rRNA) or other sequence with an ionsemiconductor sequencing platform. The term “ion semiconductorsequencing platform” refers to any device and/or method that detects theproduction of hydrogen ions during a chemical condensation reaction. Thedevice and/or method quantitates the production of hydrogen ions bychanges in the pH of a mixture and/or solution. For example, nucleicacids may be sequenced by measuring pH fluctuations in a mixture duringamplification of a nucleic acid sequence.

There are several probes or primers that may be used in accordance withthe present disclosure. These probes/primers can take on a variety ofconfigurations and may have a variety of structural components describedin more detail below. The first step probe may be an allele specificprobe or locus specific probe. “Allele specific” probe or primer refersto a probe or primer that hybridizes to a target sequence anddiscriminates between alleles or hybridizes to a target sequence and ismodified in an allele specific manner. “Locus specific” probe or primerrefers to a probe or primer that hybridizes to a target sequence in alocus specific manner, but does not necessarily discriminate betweenalleles. A locus specific primer also may be modified, i.e., extended asdescribed below, such that it includes information about a particularallele, but the locus specific primer does not discriminate betweenalleles.

In many embodiments, the probes or primers comprise one or moreuniversal priming site(s) and/or adapters, both of which are describedbelow.

A size of the primer and probe nucleic acid may vary with each portionof the probe and the total length of the probe in general varying from 5to 500 nucleotides in length. Each portion can be between 10 and 100,between 15 and 50, or 10 to 35, depending on the use and amplificationtechnique. Thus, for example, the universal priming site(s) of theprobes can each be about 15-20 nucleotides in length, or 18 nucleotides.The adapter sequences of the probes can be from 15-25 nucleotides inlength, or about 20 nucleotides. The target specific portion of theprobe can be from 15-50 nucleotides in length. In addition, the primermay include an additional amplification priming site.

In accordance with some examples of the disclosure, the allele or locusspecific probe or probes comprise a target domain substantiallycomplementary to a first domain of the target sequence. In general,probes of the present disclosure are designed to be complementary to atarget sequence (either the target sequence of the sample or to otherprobe sequences, as is described herein), such that hybridization of thetarget and the probes of the present disclosure occurs. Thiscomplementarity need not be perfect; there may be any number of basepair mismatches that will interfere with hybridization between thetarget sequence and the single stranded nucleic acids of the presentdisclosure. However, if the number of mutations is so great that nohybridization can occur under even the least stringent of hybridizationconditions, the sequence is not a complementary target sequence. Thus,“substantially complementary” as used herein means that the probes aresufficiently complementary to the target sequences to hybridize underthe selected reaction conditions.

In one embodiment the target specific portion includes a combinatorialmixture of each nucleotide at each position. In addition the primerincludes a universal priming sequence and an allele specific position.The universal priming sequence can be specific for the particularnucleotide at the allele specific position. That is, the locus-specificallele selectivity portions of the primer can be replaced with auniversal targeting domain that includes a region where each position isrepresented by a combinatorial mixture of nucleotides. One of thepositions in the universal region (not necessarily the 3′ position) ispaired with the genomic region to be analyzed.

In another example, one of the probes further comprises an adaptersequence, (sometimes referred to in the art as “zip codes” or “barcodes”). Adapters facilitate immobilization of probes to allow the useof “universal arrays.” That is, arrays (either solid phase or liquidphase arrays) are generated that contain capture probes that are nottarget specific, but rather specific to individual (preferably)artificial adapter sequences.

Thus, an “adapter sequence” is a nucleic acid that is generally notnative to the target sequence, i.e. is exogenous, but is added orattached to the target sequence. It should be noted that in thiscontext, the “target sequence” can include the primary sample targetsequence, or can be a derivative target such as a reactant or product ofthe reactions outlined herein; thus for example, the target sequence canbe a PCR product, a first ligation probe or a ligated probe in an OLAreaction, etc. The terms “barcodes,” “adapters,” “addresses,” “tags,”and “zip codes” have all been used to describe artificial sequences thatare added to amplicons to allow separation of nucleic acid fragmentpools. One exemplary form of adapters is hybridization adapters, whichcan be chosen so as to allow hybridization to the complementary captureprobes on a surface of an array. Adapters serve as unique identifiers ofthe probe and thus of the target sequence. In general, sets of adaptersand the corresponding capture probes on arrays are developed to minimizecross-hybridization with both each other and other components of thereaction mixtures, including the target sequences and sequences on thelarger nucleic acid sequences outside of the target sequences (e.g. tosequences within genomic DNA). Other forms of adapters are mass tagsthat can be separated using mass spectroscopy, electrophoretic tags thatcan be separated based on electrophoretic mobility, etc. Some adaptersequences are outlined in U.S. Ser. No. 09/940,185, filed Aug. 27, 2001,hereby incorporated by reference in its entirety to the extent thecontents thereof do not conflict with the present disclosure. Exemplaryadapters are those that meet the following criteria. They are not foundin a genome, preferably a human or microbial genome, and they do nothave undesirable structures, such as hairpin loops.

As will be appreciated by those in the art, the attachment, or joining,of the adapter sequence to the target sequence can be done in a varietyof ways. In one embodiment, the adapter sequences are added to theprimers of the reaction (extension primers, amplification primers,readout probes, genotyping primers, Rolling Circle primers, etc.) duringthe chemical synthesis of the primers. The adapter then gets added tothe reaction product during the reaction; for example, the primer getsextended using a polymerase to form the new target sequence that nowcontains an adapter sequence. Alternatively, the adapter sequences canbe added enzymatically. Furthermore, the adapter can be attached to thetarget after synthesis; this post-synthesis attachment can be eithercovalent or non-covalent. In another embodiment the adapter is added tothe target sequence or associated with a particular allele during anenzymatic step. That is, to achieve the level of specificity necessaryfor highly multiplexed reactions, the product of the specificity orallele specific reaction preferably also includes at least one adaptersequence.

One or more of the specificity primers can include a first portioncomprising the adapter sequence and a second portion comprising thepriming sequence. Extending the amplification primer results in targetsequences that comprise the adapter sequences. The adapter sequences aredesigned to be substantially complementary to capture probes.

In addition, the adapter can be attached either on the 3′ or 5′ ends, orin an internal position, depending on the configuration of the system.

In accordance with one example, the use of adapter sequences allows thecreation of more “universal” surfaces; that is, one standard array,comprising a finite set of capture probes can be made and used in anyapplication. The end-user can customize the array by designing differentsoluble target probes, which, as will be appreciated by those in theart, is generally simpler and less costly. In an exemplary embodiment,an array of different and usually artificial capture probes are made;that is, the capture probes do not have to be complementarity to knowntarget sequences. The adapter sequences can then be incorporated in thetarget probes.

As can be appreciated, the length of the adapter sequences will vary,depending on the desired “strength” of binding and the number ofdifferent adapters desired. In accordance with various examples, anadapter sequences range from about 6 to about 500 basepairs in length,or 8 to about 100 basepairs, or about 10 to about 25 basepairs.

In one example, the adapter sequence uniquely identifies the targetanalyte to which the target probe binds. That is, while the adaptersequence need not bind itself to the target analyte, the system allowsfor identification of the target analyte by detecting the presence ofthe adapter. Accordingly, following a binding or hybridization assay andwashing, the probes including the adapters are amplified. Detection ofthe adapter then serves as an indication of the presence of the targetanalyte.

In one embodiment, the adapter includes both an identifier region and aregion that is complementary to capture probes on a universal array asdescribed above. In this embodiment, the amplicon hybridizes to captureprobes on a universal array. Detection of the adapter can beaccomplished following hybridization with a probe that is complementaryto the adapter sequence. The probe can be labeled as described herein.

In general, unique adapter sequences are used for each unique targetanalyte. That is, the elucidation or detection of a particular adaptersequence allows the identification of the target analyte to which thetarget probe containing that adapter sequence bound. However, in somecases, it is possible to “reuse” adapter sequences and have more thanone target analyte share an adapter sequence.

The adapters can contain different sequences or properties that areindicative of a particular target molecule. That is, each adapter canuniquely identify a target sequence. As described above, the adapterscan be amplified to form amplicons. The adapter is detected as anindication of the presence of the target analyte, i.e. the particulartarget nucleic acid. The use of adapters in combination withamplification following a specific binding event allows for highlymultiplexed reactions to be performed.

Also, the probes are constructed so as to contain the desired primingsite or sites for the subsequent amplification scheme. For example, thepriming sites can be universal priming sites. By “universal primingsite” or “universal priming sequences” herein is meant a sequence of theprobe that will bind a primer for amplification.

By way of example, when amplification methods requiring two primers suchas PCR are used, each probe can comprise an upstream universal primingsite (UUP) and a downstream universal priming site (DUP). Again,“upstream” and “downstream” are not meant to convey a particular 5′-3′,orientation, and will depend on the orientation of the system. Only asingle UUP sequence and a single DUP sequence can be used in a probeset, although different assays or different multiplexing analysis mayutilize a plurality of universal priming sequences. In some embodiments,probe sets may comprise different universal priming sequences. Inaddition, the universal priming sites are preferably located at the 5′and 3′ termini of the target probe (or the ligated probe), as onlysequences flanked by priming sequences will be amplified.

In addition, universal priming sequences are generally chosen to be asunique as possible given the particular assays and host genomes toensure specificity of the assay. However, as will be appreciated, setsof priming sequences/primers may be used.

When two priming sequences are used, the orientation of the two primingsites can be generally different. That is, one PCR primer will directlyhybridize to the first priming site, while the other PCR primer willhybridize to the complement of the second priming site. Stateddifferently, the first priming site is in sense orientation, and thesecond priming site is in antisense orientation.

In general, highly multiplexed reactions can be performed, with all ofthe universal priming sites being the same for all reactions.Alternatively, “sets” of universal priming sites and correspondingprobes can be used, either simultaneously or sequentially. The universalpriming sites are used to amplify the modified probes to form aplurality of amplicons that are then detected in a variety of ways, asoutlined herein.

Accordingly, various examples of the present disclosure provide firsttarget probe sets. By “probe set” herein is meant a plurality of targetprobes that are used in a particular multiplexed assay. First targetprobe sets can each comprise at least a first universal priming site.

The target probe may also comprise a label sequence, i.e. a sequencethat can be used to bind label probes and is substantially complementaryto a label probe. Such system is sometimes referred to in the art as“sandwich-type” assays. That is, by incorporating a label sequence intothe target probe, which is then amplified and present in the amplicons,a label probe comprising primary (or secondary) detection labels can beadded to the mixture, either before addition to the array or after. Thisallows the use of high concentrations of label probes for efficienthybridization. It is possible to use the same label sequence and labelprobe for all target probes on an array; alternatively, different targetprobes can have a different label sequence. Similarly, the use ofdifferent label sequences can facilitate quality control; for example,one label sequence (and one color) can be used for one strand of thetarget, and a different label sequence (with a different color) for theother; and in this case only if both colors are present at the samebasic level is a positive called.

Thus, the present disclosure provides target probes that comprise any,all or any combination of universal priming sequences, bioactive agents(e.g. target specific portion(s)), adapter sequence(s), optionally anadditional amplification priming sequence and optionally labelsequences. These target probes can then added to the target sequences toform hybridization complexes. When nucleic acids are the target, thehybridization complexes can contain portions that are double stranded(the target-specific sequences of the target probes hybridized to aportion of the target sequence) and portions that are single stranded(the ends of the target probes comprising the universal primingsequences and the adapter sequences, and any unhybridized portion of thetarget sequence).

In some embodiments, the purified DNA from the sample is analyzed bySequencing by Synthesis (SBS) techniques. SBS techniques generallyinvolve the enzymatic extension of a nascent nucleic acid strand throughthe iterative addition of nucleotides against a template strand. Intraditional methods of SBS, a single nucleotide monomer may be providedto a target nucleotide in the presence of a polymerase in each delivery.However, in some of the methods described herein, more than one type ofnucleotide monomer can be provided to a target nucleic acid in thepresence of a polymerase in a delivery.

SBS can utilize nucleotide monomers that have a terminator moiety orthose that lack any terminator moieties. Methods utilizing nucleotidemonomers lacking terminators include, for example, pyrosequencing andsequencing using γ-phosphate-labeled nucleotides. In methods usingnucleotide monomers lacking terminators, the number of differentnucleotides added in each cycle can be dependent upon the templatesequence and the mode of nucleotide delivery. For SBS techniques thatutilize nucleotide monomers having a terminator moiety, the terminatorcan be effectively irreversible under the sequencing conditions used asis the case for traditional Sanger sequencing which utilizesdideoxynucleotides, or the terminator can be reversible as is the casefor sequencing methods developed by Solexa (now Illumina, Inc.). In somemethods a terminator moiety can be reversibly terminating.

SBS techniques can utilize nucleotide monomers that have a label moietyor those that lack a label moiety. Accordingly, incorporation events canbe detected based on a characteristic of the label, such as fluorescenceof the label; a characteristic of the nucleotide monomer such asmolecular weight or charge; a byproduct of incorporation of thenucleotide, such as release of pyrophosphate; or the like. Inembodiments, where two or more different nucleotides are present in asequencing reagent, the different nucleotides can be distinguishablefrom each other, or alternatively, the two or more different labels canbe the indistinguishable under the detection techniques being used. Forexample, the different nucleotides present in a sequencing reagent canhave different labels and they can be distinguished using appropriateoptics as exemplified by the sequencing methods developed by Solexa (nowIllumina, Inc.). However, it is also possible to use the same label forthe two or more different nucleotides present in a sequencing reagent orto use detection optics that do not necessarily distinguish thedifferent labels. Thus, in a doublet sequencing reagent having a mixtureof A/C both the A and C can be labeled with the same fluorophore.Furthermore, when doublet delivery methods are used all of the differentnucleotide monomers can have the same label or different labels can beused, for example, to distinguish one mixture of different nucleotidemonomers from a second mixture of nucleotide monomers. For example,using the [First delivery nucleotide monomers]+[Second deliverynucleotide monomers] nomenclature set forth above and taking an exampleof A/C+(1/T), the A and C monomers can have the same first label and theG and T monomers can have the same second label, wherein the first labelis different from the second label. Alternatively, the first label canbe the same as the second label and incorporation events of the firstdelivery can be distinguished from incorporation events of the seconddelivery based on the temporal separation of cycles in an SBS protocol.Accordingly, a low resolution sequence representation obtained from suchmixtures will be degenerate for two pairs of nucleotides (T/G, which iscomplementary to A and C, respectively; and C/A which is complementaryto G/T, respectively).

Some embodiments include pyrosequencing techniques. Pyrosequencingdetects the release of inorganic pyrophosphate (PPi) as particularnucleotides are incorporated into the nascent strand (Ronaghi, M.,Karamohamed, S., Pettersson, B., Uhlen, M. and Nyren, P. (1996)“Real-time DNA sequencing using detection of pyrophosphate release.”Analytical Biochemistry 242(1), 84-9; Ronaghi, M. (2001) “Pyrosequencingsheds light on DNA sequencing.” Genome Res. 11(1), 3-11; Ronaghi, M.,Uhlen, M. and Nyren, P. (1998) “A sequencing method based on real-timepyrophosphate.” Science 281(5375), 363; U.S. Pat. No. 6,210,891; U.S.Pat. No. 6,258,568 and U.S. Pat. No. 6,274,320, the disclosures of whichare incorporated herein by reference in their entireties). Inpyrosequencing, released PPi can be detected by being immediatelyconverted to adenosine triphosphate (ATP) by ATP sulfurylase, and thelevel of ATP generated is detected via luciferase-produced photons.

In another example type of SBS, cycle sequencing is accomplished bystepwise addition of reversible terminator nucleotides containing, forexample, a cleavable or photobleachable dye label as described, forexample, in U.S. Pat. No. 7,427,67, U.S. Pat. No. 7,414,1163 and U.S.Pat. No. 7,057,026, the disclosures of which are incorporated herein byreference. This approach is being commercialized by Solexa (now IlluminaInc.), and is also described in WO 91/06678 and WO 07/123,744 (filed inthe United States patent and trademark Office as U.S. Ser. No.12/295,337), each of which is incorporated herein by reference in theirentireties. The availability of fluorescently-labeled terminators inwhich both the termination can be reversed and the fluorescent labelcleaved facilitates efficient cyclic reversible termination (CRT)sequencing. Polymerases can also be co-engineered to efficientlyincorporate and extend from these modified nucleotides.

In other embodiments, Ion Semiconductor Sequencing is utilized toanalyze the purified DNA from the sample. Ion Semiconductor Sequencingis a method of DNA sequencing based on the detection of hydrogen ionsthat are released during DNA amplification. This is a method of“sequencing by synthesis,” during which a complementary strand is builtis based on the sequence of a template strand.

For example, a microwell containing a template DNA strand to besequenced can be flooded with a single species of deoxyribonucleotide(dNTP). If the introduced dNTP is complementary to the leading templatenucleotide it is incorporated into the growing complementary strand.This causes the release of a hydrogen ion that triggers a hypersensitiveion sensor, which indicates that a reaction has occurred. If homopolymerrepeats are present in the template sequence multiple dNTP moleculeswill be incorporated in a single cycle. This leads to a correspondingnumber of released hydrogens and a proportionally higher electronicsignal.

This technology differs from other sequencing technologies in that nomodified nucleotides or optics are used. Ion semiconductor sequencingmay also be referred to as ion torrent sequencing, pH-mediatedsequencing, silicon sequencing, or semiconductor sequencing. Ionsemiconductor sequencing was developed by Ion Torrent Systems Inc. andmay be performed using a bench top machine. It is believed that hydrogenion release occurs during nucleic acid amplification because of theformation of a covalent bond and the release of pyrophosphate and acharged hydrogen ion. Ion semiconductor sequencing exploits these factsby determining if a hydrogen ion is released upon providing a singlespecies of dNTP to the reaction.

For example, microwells on a semiconductor chip that each contain onesingle-stranded template DNA molecule to be sequenced and one DNApolymerase can be sequentially flooded with unmodified A, C, G or TdNTP. The hydrogen ion that is released in the reaction changes the pHof the solution, which is detected by a hypersensitive ion sensor. Theunattached dNTP molecules are washed out before the next cycle when adifferent dNTP species is introduced.

Beneath the layer of microwells is an ion sensitive layer, below whichis a hypersensitive ISFET ion sensor. All layers are contained within aCMOS semiconductor chip, similar to that used in the electronicsindustry. Each released hydrogen ion triggers the ISFET ion sensor. Theseries of electrical pulses transmitted from the chip to a computer istranslated into a DNA sequence, with no intermediate signal conversionrequired. Each chip contains an array of microwells with correspondingISFET detectors. Because nucleotide incorporation events are measureddirectly by electronics, the use of labeled nucleotides and opticalmeasurements are avoided.

An example of a Ion Semiconductor Sequencing technique suitable for usein the methods of the provided disclosure is Ion Torrent sequencing(U.S. Patent Application Numbers 2009/0026082, 2009/0127589,2010/0035252, 2010/0137143, 2010/0188073, 2010/0197507, 2010/0282617,2010/0300559), 2010/0300895, 2010/0301398, and 2010/0304982), thecontent of each of which is incorporated by reference herein in itsentirety to the extent such contents do not conflict with the presentdisclosure. In Ion Torrent sequencing, DNA is sheared into fragments ofapproximately 300-800 base pairs, and the fragments are blunt ended.Oligonucleotide adaptors are then ligated to the ends of the fragments.The adaptors serve as primers for amplification and sequencing of thefragments. The fragments can be attached to a surface and are attachedat a resolution such that the fragments are individually resolvable.Addition of one or more nucleotides releases a proton (H⁺), which signaldetected and recorded in a sequencing instrument. The signal strength isproportional to the number of nucleotides incorporated. User guidesdescribe in detail the Ion Torrent protocol(s) that are suitable for usein methods of the disclosure, such as Life Technologies' literatureentitled “Ion Sequencing Kit for User Guide v. 2.0” for use with theirsequencing platform the Personal Genome Machine™ (PCG), the contents ofwhich are incorporated herein by reference, to the extent such contentsdo not conflict with the present disclosure.

In accordance with various examples, Ion Semiconductor Sequencing isused to maximize detection of specific microorganisms by sequencing, forexample, 16S rRNA hypervariable regions on the Ion Torrent PGM platform(Life Technologies, Carlsbad, Calif.). A primary PCR step is carried outusing chimeric primers containing a sequence specific portion foramplifying the exons 16S rRNA hypervariable regions interest along withadapter sequences for sequencing analysis. Suitable sequence specificprimers can be designed using any suitable method. The primaryconsideration is the Tm of the sequence specific portion. For example,primers with target specific Tm values ranging from about 52° C. toabout 68° C. may generate successful amplification products withchimeric oligonucleotides. Another consideration for primer design isthe size of the amplicon.

In some embodiments, as a part of the sample preparation process,“barcodes” may be associated with each sample. In this process, shortoligos are added to primers, where each different sample uses adifferent oligo in addition to a primer.

The term “library”, as used herein refers to a library of genome-derivedsequences. The library may also have sequences allowing amplification ofthe “library” by the polymerase chain reaction or other in vitroamplification methods well known to those skilled in the art. Thelibrary may also have sequences that are compatible with next-generationhigh throughput sequencers such as an ion semiconductor sequencingplatform.

In certain embodiments, the primers and barcodes are ligated to eachsample as part of the library generation process. Thus during theamplification process associated with generating the ion ampliconlibrary, the primer and the short oligo are also amplified. As theassociation of the barcode is done as part of the library preparationprocess, it is possible to use more than one library, and thus more thanone sample. Synthetic DNA barcodes may be included as part of theprimer, where a different synthetic DNA barcode may be used for eachlibrary. In some embodiments, different libraries may be mixed as theyare introduced to a flow cell, and the identity of each sample may bedetermined as part of the sequencing process. Sample separation methodscan be used in conjunction with sample identifiers. For example a chipcould have 4 separate channels and use 4 different barcodes to allow thesimultaneous running of 16 different samples.

In some embodiments, the method of the present disclosure comprisesclassifying the species or genus of the microorganism with acomputer-based genomic analysis of the sequence data from the ionsemiconductor sequencing platform. The method may further comprisegenerating a report with the species of microorganisms identified andantibiotic resistance information for each species. Exemplary systemsand methods for characterizing, identifying, and/or classifying themicroorganisms are discussed below.

In some aspects of the present disclosure, the computer-based genomicanalysis makes use of a procedural algorithm. By way of particularexample, an Ion Sequencing data can be imported into CLC Workbench andthe sequences sorted.

Sequences that are less than 100 bp in length can be removed. The entiredata set (e.g., >100 bp) is then BLASTed to a local 16S library of namedbacteria or other type of microorganism. In the case of bacteria, thelocal 16S library can be compiled from data available from the NationalCenter for Biotechnology Information (NCBI). The resulting data can besorted by BLAST hit length. The distribution of the sequence reads fromthe sequencer is analyzed to determine an appropriate cut-off to obtaina significant number of reads. Less than 20 reads is can be deemed notacceptable. Generally, hundreds if not thousands of high quality longreads are included. The returned species greater than the cut-off can betabulated for the number of times they occur as a BLAST result.Typically, sequences can be present 5 or more times and can constituteat least 1% of the sample to be reported. Any sequence that does notmeet both of these requirements may not be reported. Depending on thecut-off used, a confidence percentage is applied to the resultingspecies, genus, or microorganism calls. This data may be presentedgraphically. In one example, a maximum of six of the top species with acomplete listing in tabular format is reported. Treatment (e.g.,antibacterial, antifungal, antiviral, and/or antiprotozoal)susceptibilities for each genus/species/microorganism characterized oridentified may also be reported. The references for all of the treatmentsusceptibilities may be listed in the report.

Classification of bacteria has been greatly revised by analysis ofnucleic acid sequences. The section below contains a classification ofbacteria that are human pathogens that may be identified in accordancewith the present disclosure.

Gram-Positive Eubacteria Actinobacteria

Actinobacteria are high G+C Gram-positive eubacteria.order: Actinomycetales

-   -   suborder: Actinomycineae        -   family: Actinomyecetaceae            -   Actinomyces israelii (Streptothrix israeli Kruse 1896)                Lachner-Sandoval 1898 (actinomycosis)            -   Actinomyces naeslundi Thompson & Lovestedt 1951                (actinomycosis)            -   Actinomyces meyeri (Actinobacterium meyeri                Prévot 1938) E. P. Cato et al. 1984 (actinomycosis)            -   Actinomyces odontolyticus Batty 1958 (actinomycosis)            -   Actinomyces viscosus (Odontomyces viscosus Howell et                al. 1965) Georg et al. 1969 (actinomycosis)    -   suborder: Propionibacterineae        -   family: Propionibacteriaceae            -   Propionibacterium acnes (Bacillus acnes Gilchrist 1900)                Douglas & Gunter 1946 (actinomycosis)    -   suborder; Micrococcineae        -   family: Cellulomonadaceae            -   Tropheryma whipplei (Tropheryma whippelii 1991) La Scola                et al. 2001 (Whipple disease)    -   suborder: Streptosporangineae        -   family: Thermomonosporaceae            -   Actinomadura madurae (Streptothrix madurae Vincent 1894)                Lechevalier and Lechevalier 1968 (actinomycetoma)            -   Actinomadura pelletieri (Micrococcus pelletieri                Layeran 1906) Lechevalier and Lechevalier 1968                (actinomycetoma)        -   Nocardiopsaceae            -   Nocardiopsis dassonvillei (Streptothrix dassonvillei                Brocq-Rousseau 1904) Meyer 1976 (actinomycetoma)    -   suborder: Streptomycineae        -   family: Streptomycetaceae            -   Streptomyces somaliensis (Indiella somaliensis                Brumpt 1906) Waksman and Henrici 1948 (actinomycetoma)    -   suborder: Corynebacterineae        -   family: Nocardiaceae            -   Nocardia asteroides (Cladothrix asteroides                Eppinger 1891) Blanchard 1896 (nocardiosis,                actinomycetoma)            -   Nocardia brasiliensis (Discomyces brasiliensis                Lindenberg 1909) Pinoy 1913 (nocardiosis,                actinomycetoma)            -   Nocardia otitidiscaviarum Snijders 1924 (nocardiosis,                actinomycetoma)            -   Nocardia transvalensis Pijper and Pullinger 1927                (nocardiosis)            -   Rhodococcus equi (Corynebacterium equi Magnusson 1923)                Goodfellow & Alderson 1977        -   family: Mycobacteriaceae            -   Mycobacterium leprae Hansen, 1874 (leprosy)            -   Mycobacterium tuberculosis complex                -   Mycobacterium tuberculosis Zopf 1883 (tuberculosis)                -   Mycobacterium africanum Castets et al. 1969                    (tuberculosis)                -   Mycobacterium bovis Karlson & Lessel 1970                    (tuberculosis)            -   Mycobacterium avium complex (MAC)                -   Mycobacterium avium Chester 1901                -   Mycobacterium intracellulare (Nocardia                    intracellularis Cuttino and McCabe 1949) Runyon 1965                -   Mycobacterium scrofulaceum Prissick and Masson 1956            -   Mycobacterium fortuitum complex (MFC)                -   Mycobacterium fortuitum da Costa Cruz 1938                -   Mycobacterium chelonae Bergey et al. 1923            -   Mycobacterium kansasii Hauduroy 1955            -   Mycobacterium ulcerans MacCallum et al. 1950 (Buruli                ulcer)            -   Mycobacterium abscessus Moore and Frerichs 1953            -   Mycobacterium haemophilum Sompolinsky et al. 1978            -   Mycobacterium marinum Aronson 1926            -   Mycobacterium simiae Karassova et al. 1965            -   Mycobacterium xenopi Schwabacher 1959        -   family: Corynebacteriaceae            -   Corynebacterium diphtheriae (Bacillus diphtheriae                Kruse 1886) Lehmann and Neumann 1896 (diphtheria)            -   Corynebacterium minutissimum Sarkany et al. 1962                (erythrasma)            -   Corynebacterium jeikeium Jackman et al. 1988                order: Bifidobacteriales    -   family: Bifidobacteriaceae        -   Gardnerella vaginalis (Haemophilus vaginalis Gardner and            Dukes 1955) Greenwood and Pickett 1980 (bacterial vaginitis)

Firmicutes

Firmicutes are usually described as low G+C gram-positive Eubacteria,but they also include Eubacteria that lack a cell wall (e.g.,Mycoplasma)class: Bacilli

-   -   order: Lactobacillales        -   family: Streptococcaceae            -   Streptococcus pyogenes Rosenbach 1884 (Lancefield Group                A; (3-hemolytic) (scarlet fever, erysipelas, rheumatic                fever, pharyngitis, cellulitis)            -   Streptococcus agalactiae Lehmann and Neumann 1896                (Lancefield Group B; β-hemolytic) (sepsis of the                newborn)            -   Streptococcus dysgalactiae group                -   S. dysgalactiae Diernhofer 1932                -   S. equi Sand and Jensen 1888 (includes S. equi                    zooepidemicus)            -   Streptococcus equinus Andrewes and Horder 1906 (aka S.                bovis; γ-hemolytic)            -   Streptococcus canis Devriese et al. 1986            -   Streptococcus pneumoniae (Micrococcus pneumoniae                Klein 1884) Chester 1901 (α-hemolytic); pneumococcal                infection)            -   Streptococcus viridans group (α-hemolytic or                non-hemolytic)                -   S. mitis Andrewes and Horder 1906                -   S. mutans Clarke 1924                -   S. oxalis Bridge and Sneath 1982                -   S. sanguinis White and Niven 1946                -   S. sobrinus Coykendall 1974                -   Streptococcus milleri group (Lancefield Group F)                -    S. anginosus Andrewes and Horder 1906                -    S. constellatus (Diplococcus constellatus                    Prevot 1924) Holdeman & Moore 1974                -    S. intermedius Prevot 1925    -   family: Enterococcaceae        -   Enterococcus faecalis (Streptococcus faecalis Andrewes and            Horder 1906) Schleifer & Kilpper-Balz 1984 (γ-hemolytic)        -   Enterococcus faecium (Streptococcus faecium            Orla-Jensen 1919) Schleifer & Kilpper-Balz 1984            (γ-hemolytic; vancomycin-resistant enterococcus)    -   order: Bacillales        -   family: Staphylococcaceae            -   Staphylococcus aureus Rosenbach 1884 (cellulitis,                Staphylococcal scalded skin syndrome, toxic shock                syndrome, food poisoning)            -   Staphylococcus epidermidis (Albococcus epidermidis                Winslow & Winslow 1908) Evans 1916            -   Staphylococcus saprophyticus Fairbrother 1940 (urinary                tract infection)        -   family: Bacillaceae            -   Bacillus anthracis Cohn 1872 (anthrax)            -   Bacillus cereus Frankland & Frankland 1887 (food                poisoning)        -   family: Listeriaceae            -   Listeria monocytogenes (Bacterium monocytogenes Murray                et al. 1926) Pirie 1940 (Listeriosis)                class: Clostridia    -   order: Clostridiales        -   family: Clostridiaceae            -   Clostridium botulinum (Bacillus botulinus van                Ermengem 1896) Bergey et al. 1923 (botulism)            -   Clostridium difficile (Bacillus difficilis Hall &                O'Toole 1935) Prevot 1938 (pseudomembranous colitis)            -   Clostridium perfringens (Bacillus perfringens Veillon &                Zuber 1898) Hauduroy et al. 1937 (gas gangrene,                clostridial necrotizing enteritis)            -   Clostridium tetani (Bacillus tetani F11igge 1886) Bergey                et al. 1923 (tetanus)        -   family: Peptostreptococcaceae            -   Peptostreptococcus sp.                class: Mollicutes                This group of eubacteria is characterized by the absence                of a cell wall (aphragmabacteria). They were previously                classified as Tenericutes, a sister group to Firmicutes,                before being reassigned as a class within Firmicutes.    -   order: Mycoplasmatales        -   family: Mycoplasmataceae            -   Mycoplasma genitalium Tully et al., 1983            -   Mycoplasma pneumoniae Somerson et al., 1963 (mycoplasmal                pneumonia, primary atypical pneumonia)            -   Mycoplasma arthriditis            -   Mycoplasma fermentans            -   Ureaplasma urealyticum Shepard et al., 1974 (Ureaplasma                infection, urethritis)    -   order: Anaeroplasmatales (or Erysipelotrichales)        -   family: Erysipelotrichaceae            -   Erysipelothrix rhusiopathiae (Bacterium rhusiopathiae                Migula 1900) Buchanan 1918 (erysipeloid)    -   order: Acholeplasmatales        -   family: Acholeplasmataceae            -   Acholeplasma axanthum            -   Acholeplasma brassicae            -   Acholeplasma cavigenitalium            -   Acholeplasma entomophilum            -   Acholeplasma equifetale            -   Acholeplasma florum            -   Acholeplasma granularum            -   Acholeplasma hippikon            -   Acholeplasma laidlawii            -   Acholeplasma modicum            -   Acholeplasma morum            -   Acholeplasma multilocale            -   Acholeplasma oculi            -   Acholeplasma palmae            -   Acholeplasma parvum            -   Acholeplasma pleciae            -   Acholeplasma seiffertii            -   Acholeplasma vituli

Bacteroidetes

class: Bacteroidetes

-   -   order: Bacteroidales        -   family: Bacteroidaceae            -   Bacteroides fragilis (Bacillus fragilis Veillon and                Zuber 1898) Castellani and Chalmers 1919        -   family: Porphyromonadaceae            -   Tannerella forsythia (Bacteroides forsythus Tanner et                al. 1986) Sakamoto et al. 2002            -   Porphyromonas gingivalis (Bacteroides gingivalis                Coykendall et al. 1980) Shah and Collins 1988        -   family: Prevotellaceae            -   Prevotella intermedia (Bacteroides melaminogenicus                intermedius Holdeman and Moore 1970) Shah and Collins                1990                class: Flavobacteria    -   order: Flavobacteriaceae        -   family: Flavobacteriales            -   Capnocytophaga canimorsus Brenner et al. 1990

Chlamydiae

-   -   order: Chlamydiales        -   family: Chlamydiaceae            -   Chlamydia trachomatis (Rickettsia trachomae                Busacca 1935) Rake 1957 (lymphogranuloma venereum,                trachoma)            -   Chlamydophila psittaci (Rickettsia psittaci Lillie 1930)                Everett et al. 1999 (psittacosis)            -   Chlamydophila pneumoniae (Chlamydia pneumoniae Grayston                et al. 1989) Everett et al. 1999

Fusobacteria

-   -   order: Fusobacteriales        -   family: Fusobacteriaceae            -   Fusobacterium necrophorum (Bacillus necrophorus                Flugge 1886) Moore and Holdeman 1969 (Lemierre's                syndrome)            -   Fusobacterium nucleatum (Bacillus fusiformis Veillon and                Zuber 1898) Knorr 1922                -   Fusobacterium nucleatum nucleatum Knorr 1922                -   Fusobacterium nucleatum polymorphum (Fusobacterium                    polymorphum Knorr 1922) Dzink et al. 1990            -   Streptobacillus moniliformis (Streptothrix muris ratti                Schottmuller 1914) Levaditi et al. 1925 (Actinobacillus                muris Wilson and Miles 1955; rat bite fever)

Proteobacteria

class: Alpha Proteobacteria

-   -   order: Rickettsiales        -   family: Rickettsiaceae            -   Rickettsia—spotted fever group                -   Rickettsia rickettsii (Dermacentroxenus rickettsii                    Wolbach 1919) Brumpt 1922 (Rocky Mountain spotted                    fever)                -   Rickettsia conorii Brumpt 1932 (Boutonneuse fever)                -   Rickettsia akari Huebner et al. 1946                    (rickettsialpox)            -   Rickettsia—typhus group                -   Rickettsia typhi (Dermacentroxenus typhi Wolbach and                    Todd 1920) Philip 1943 (murine typhus)                -   Rickettsia prowazekii da Rocha-Lima 1916 (epidemic                    typhus)            -   Orientia tsutsugamushi (Theileria tsutsugamushi                Hayashi 1920) Tamura et al. 1995 (scrub typhus)        -   family: Anaplasmataceae (or Ehrlichiaceae) (Ehrlichiosis and            Anaplasmosis)            -   Anaplasma phagocytophilum (Rickettsia phagocytophila                ovis Foggie 1949) Dumler et al. 2001 (human granulocytic                ehrlichiosis)            -   Ehrlichia chaffeensis Anderson et al. 1992 (human                monocytic ehrlichiosis)    -   order Rhizobiales        -   family: Brucellaceae            -   Brucella abortus (Bacterium abortus Schmidt 1901) Meyer                and Shaw 1920 (Brucellosis)        -   family: Bartonellaceae            -   Bartonella bacilliformis (Bartonia bacilliformis Strong                et al. 1913) Strong et al. 1915 (Carrion's disease)            -   Bartonella henselae (Rochalimaea henselae Regnery et                al. 1992) Brenner et al. 1993 (cat scratch fever;                bacillary angiomatosis)            -   Bartonella quintana (Rickettsia quintana Schmincke 1917)                Brenner et al. 1993 (trench fever; bacillary                angiomatosis)                class: Beta Proteobacteria    -   order: Neisseriales        -   family: Neisseriaceae            -   Neisseria meningitidis (Micrococcus meningitidis                cerebrospinalis Albrecht & Ghon 1901) Murray 1929                (meningococcal disease, Waterhouse-Friderichsen                syndrome)            -   Neisseria gonorrhoeae (Merismopedia gonorrhoeae                Zopf 1885) Trevisan 1885 (gonorrhea)            -   Eikenella corrodens (Bacteroides corrodens Eiken 1958)                Jackson and Goodman 1972            -   Kingella kingae (Moraxella kingii Henriksen and                Bovre 1968) Henriksen and Bovre 1976    -   order: Burkholderiales        -   family: Burkholderiaceae            -   Burkholderia pseudomallei group                -   B. pseudomallei (Bacillus pseudomallei                    Whitmore 1913) Yabuuchi et al. 1993 (aka Pseudomonas                    pseudomallei Haynes 1957; melioidosis)                -   B. mallei (Bacillus mallei Zopf 1885) Yabuuchi et                    al. 1993 (aka Pseudomonas mallei Redfearn et al.                    1966; glanders)            -   Burkholderia cepacia complex                -   B. cepacia (Pseudomonas cepacia Burkholder 1950)                    Yabuuchi et al. 1993                -   B. vietnamiensis Gillis et al. 1995                -   B. multivorans Vandamme et al. 1997                -   B. stabilis Vandamme et al. 2000                -   B. ambifaria Coenye et al. 2001                -   B. anthina Vandamme et al. 2002                -   B. cenocepacia Vandamme et al. 2003                -   B. dolosa Vermis et al. 2004                -   B. pyrrocinia (Pseudomonas pyrrocinia Imanaka et                    al. 1965) Vandamme et al. 1997    -   family: Alcaligenaceae        -   Bordetella pertussis (Hemophilus pertussis Bergey et            al. 1923) Moreno-López 1952 (pertussis or whooping cough)        -   Bordetella parapertussis (Bacillus parapertussis Eldering            and Kendrick 1938) Moreno-López 1952 (parapertussis)    -   Family: Ralstoniaceae        -   Ralstonia basilensis        -   Ralstonia campinensis        -   Ralstonia eutropha        -   Ralstonia gilardii        -   Ralstonia insidiosa        -   Ralstonia mannitolilytica        -   Ralstonia metallidurans        -   Ralstonia paucula        -   Ralstonia pickettii        -   Ralstonia respiraculi        -   Ralstonia solanacearum        -   Ralstonia syzygii        -   Ralstonia taiwanensis    -   order: Nitrosomonadales        -   family: Spirillaceae            -   Spirillum minus (Rat-bite fever)                class: Gamma Proteobacteria    -   order: Enterobacteriales        -   family: Enterobacteriaceae            -   Enterobacter cloacae (Bacillus cloacae Jordan 1890)                Hormaeche and Edwards 1960            -   Escherichia coli (Bacillus coli Migula 1895) Castellani                and Chalmers 1919            -   Klebsiella granulomatis (Calymmatobacterium granulomatis                Arago & Vianna 1913) Carter et al. 1999 (granuloma                inguinale or donovanosis)            -   Klebsiella oxytoca (Bacillus oxytocus perniciosus                Flügge 1886) Lautrop 1956            -   Klebsiella pneumoniae (Hyalococcus pneumoniae                Schroeter 1886) Trevisan 1887 (rhinoscleroma, Klebsiella                pneumonia)            -   Plesiomonas shigelloides (Pseudomonas shigelloides                Bader 1954) Habs and Schubert 1962 (aka Aeromonas                shigelloides Ewing et al. 1961)            -   Proteus mirabilis Hauser 1885            -   Proteus vulgaris Hauser 1885            -   Salmonella enterica (Bacillus cholerae-suis Smith 1894)                Kauffmann & Edwards 1952 (typhoid fever, paratyphoid                fever, Salmonellosis)            -   Serratia marcescens Bizio 1823 (Serratia infection)            -   Shigella dysenteriae (Bacillus dysentericus Shiga 1897)                Castellani & Chalmers 1919 (Shigellosis, bacillary                dysentery)            -   Shigella flexneri Castellani & Chalmers 1919                (Shigellosis, bacillary dysentery)            -   Shigella sonnei (Bacterium sonnei Levine 1920) Weldin                1927 (Shigellosis, bacillary dysentery)            -   Yersinia enterocolitica (Bacterium enterocoliticum                Schleifstein & Coleman 1939) Frederiksen 1964            -   Yersinia pestis (Bacterium pestis Lehmann &                Neumann, 1896) van Loghem 1944 (aka Pasteurella pestis                Bergey et al. 1923; plague/bubonic plague)            -   Yersinia pseudotuberculosis (Bacillus pseudotuberkulosis                Pfeiffer 1889) Smith & Thal 1965    -   order: Cardiobacteriales        -   family: Cardiobacteriaceae            -   Cardiobacterium hominis Slotnick and Dougherty 1964    -   order: Legionellales        -   family: Legionellaceae            -   Legionella pneumophila Brenner et al. 1979                (Legionellosis)            -   Legionella longbeachae McKinney et al. 1982                (Legionellosis)        -   family: Coxiellaceae            -   Coxiella burnetii (Rickettsia burneti Derrick 1939)                Philip 1948 (Q fever)    -   order: Pasteurellales        -   family: Pasteurellaceae            -   Haemophilus influenzae (Bacterium influenzae Lehmann &                Neumann 1896) Winslow et al. 1917 (Haemophilus                meningitis, Brazilian purpuric fever)            -   Haemophilus ducreyi (Bacillus ulceris cancrosi                Kruse 1896) Bergey et al. 1923 (chancroid)            -   Pasteurella multocida (Bacterium multocidum Lehmann and                Neumann 1899) Rosenbusch and Merchant 1939                (Pasteurellosis)            -   Actinobacillus ureae (Pasteurella ureae Jones 1962)                Mutters et al. 1986 (Actinobacillosis)            -   Actinobacillus hominis Friis-Mller 1985                (Actinobacillosis)            -   Aggregatibacter actinomycetemcomitans (Bacterium                actinomycetem comitans Klinger 1912) Norskov-Lauritsen                and Kilian 2006 (aka Actinobacillus                actinomycetemcomitans Topley and Wilson 1929)    -   order: Pseudomonadales        -   family: Pseudomonadaceae            -   Pseudomonas aeruginosa (Bacterium aeruginosum                Schroter 1872) Migula 1900 (Pseudomonas infection)        -   family: Moraxellaceae            -   Moraxella catarrhalis (Mikrokkokus catarrhalis Frosch                and Kolle 1896) Henriksen and Bovre 1968 (aka                Branhamella catarrhalis Catlin 1970)            -   Acinetobacter baumannii Bouvet and Grimont 1986    -   order: Thiotrichales        -   family: Francisellaceae            -   Francisella tularensis (Bacterium tularense McCoy and                Chapin 1912) Dorofe'ev 1947 (tularemia)    -   order: Vibrionales        -   family: Vibrionaceae            -   Vibrio cholerae Pacini 1854 (cholera)            -   Vibrio vulnificus (Beneckea vulnifica Reichelt et                al. 1979) Farmer 1980            -   Vibrio parahaemolyticus (Pasteurella parahaemolytica                Fujino et al. 1951) Sakazaki et al. 1963 (aka Beneckea                parahaemolytica Baumann et al. 1971)    -   order: Xanthomonadales        -   family: Xanthomonadaceae            -   Stenotrophomonas maltophilia (Pseudomonas maltophilia                Hugh and Ryschenkow 1961) Palleroni & Bradbury 1993                class: Epsilon Proteobacteria    -   order: Campylobacterales        -   family: Campylobacteraceae            -   Campylobacter jejuni (Vibrio jejuni Jones et al. 1931)                Veron & Chatelain 1973 (Campylobacteriosis)            -   Campylobacter coli (Vibrio coli Doyle 1948) Veron and                Chatelain 1973            -   Campylobacter lari (Campylobacter laridis Benjamin et                al. 1983) Benjamin et al. 1984            -   Campylobacter fetus (Vibrio fetus Smith and Taylor 1919)                Sebald and Veron 1963        -   family: Helicobacteraceae            -   Helicobacter pylori (Campylobacter pyloridis Marshall et                al. 1985) Goodwin et al. 1989 (peptic ulcer)            -   Helicobacter cinaedi (Campylobacter cinaedi Totten et                al. 1988) Vandamme et al. 1991            -   Helicobacter fennelliae (Campylobacter fennelliae Totten                et al. 1988) Vandamme et al. 1991

Spirochaetes

-   -   order: Spirochaetales        -   family: Spirochaetaceae            -   Treponema pallidum (Spirochaeta pallida Schaudinn and                Hoffmann 1905) Schaudinn 1905                -   Treponema pallidum pallidum (syphilis)                -   Treponema pallidum endemicum (bejel)                -   Treponema pallidum pertenue (yaws)            -   Treponema carateum (pinta)            -   Treponema denticola (Spirochaete denticola Flugge 1886)                Chan et al. 1993            -   Borrelia recurrentis (Spirochaete recurrentis                Lebert 1874) Bergey et al. 1925 (relapsing fever)            -   Borrelia burgdorferi Johnson et al. 1984 (Lyme disease,                erythema chronicum migrans, neuroborreliosis)        -   family: Leptospiraceae            -   Leptospira interrogans (Spirochaeta interrogans                Stimson 1907) Wenyon 1926 (leptospirosis)

In certain aspects, the disclosed system and methods are used to analyzea dental sample and any of the following organism genera may bedetected: Bacteroides, Tannerella, Prevotella, Peptostreptococcus,Streptococcus, Staphylococcus, Porphyromonas, Fusobacterium,Clostridium, Treponema, Atopobium, Cryptobacterium, Eubacterium,Mogibacterium, Filifactor, Dialister, Centipeda, Selenomonas,Granulicatella, and Kingella and/or other bacteria, viruses, fungi,and/or protozoa. A “dental sample” may comprise a tooth, a soft tissue,and/or dental pulp.

In other aspects, the disclosed system and methods are used to analyze ajoint sample and any of the following organism genera may be detected:Staphylococcus, Streptococcus, Kingella, Aeromonas, Mycobacterium,Actinomyces, Fusobacterium, Salmonella, Haemophilus, Borrelia,Neisseria, Escherichia, Brucella, Pseudomonas, Mycoplasma, Salmonella,Propionibacterium, Acinetobacter, Treponema, and Erysipelothrix and/orother bacteria, viruses, fungi, and/or protozoa. A “joint sample” maycomprise tissue and/or fluid (e.g., synovial fluid) removed from ajoint.

In yet other aspects, the disclosed system and methods are used toanalyze a blood, sample and any of the following organism genera may bedetected: Capnocytophaga, Rickettsia, Staphylococcus, Streptococcus,Neisseria, Mycobacterium, Klebsiella, Haemophilus, Fusobacterium,Chlamydia, Enterococcus, Escherichia, Enterobacter, Proteus, Legionella,Pseudomonas, Clostridium, Listeria, Serratia, and Salmonella and/orother bacteria, viruses, fungi, and/or protozoa. A “blood sample” maycomprise blood, serum, and/or plasma.

Certain microorganisms are “nonculturable” pathogens. As used herein,the term “nonculturable” refers to microorganisms that are alive but donot produce visible colonies on classical liquid or solid media (e.g.,Luria Broth, thioglycollate broth, blood culture, etc.) within 96 hoursafter inoculation at about 30° C. under aerobic or anaerobic conditions.Examples of such nonculturable microorganisms are Bartonella henselae,the causative agent of bacillary angiomatosis; Tropheryma whipplei, theetiologic agent in Whipple's disease; and Bartonella quintana andCoxiella burnetii, which are both associated with endocarditis.Exemplary methods of the present disclosure may be used to identify suchnonculturable pathogens in a biological sample.

Exemplary methods of the present disclosure may also be used to identifya “pathogenic community of microorganisms.” As used herein, a“pathogenic community of microorganisms” is a group of microorganismswhere the individuals are not pathogenic but together they constitute aninvasive, pathogenic population. The study of population-level virulencetraits among communal bacteria represents an emerging discipline in thefield of bacterial pathogenesis. It has become clear that bacteriaexhibit many of the hallmarks of multicellular organisms when they aregrowing as biofilms and communicating among each other usingquorum-sensing systems. Each of these population-level behaviorsprovides for multiple expressions of virulence that individualfree-swimming bacteria do not possess. Population-level virulence traitsare often associated with chronic or persistent infections, whereasindividual bacterial virulence traits are generally associated withacute infections.

In certain aspects, the present disclosure provides a method and kitthat qualifies as a high complexity test under CLIA guidelines and maybe validated as a Laboratory Developed Test (LDT). As an LDT, thediagnostic system and methods may be required to meet several complianceguidelines regarding accuracy, validity, and performance parameters.

In certain aspects, the following control checks are in place for thedisclosed system and methods:

Run-to-Run Controls

Sample Quality—The quality and quantity of received samples arescrutinized for visible signs of contamination or other concerns thatwould preclude processing. Hemolyzed blood samples, clearly contaminatedtissues or fluids, and inappropriately shipped or stored samples arerejected from analysis.

DNA Extraction—DNA is extracted from the submitted samples and the totalrecovered DNA content is analyzed for concentration and purity. If aminimum of about 5 ng/μL total DNA concentration is not obtainedanalysis may not be performed as the quantity or quality of the providedsample may not be sufficient. Furthermore, the 260λ/280λ and 260λ/230λratios are observed to assess for contaminating proteins or otherpotential inhibitors.

Molecular Tagging and Amplification—DNA amplification reactions areperformed in parallel with negative amplification controls for eachpatient sample and with a master positive control of a known microbialsample from the ATCC bioresource bank. The positive control species isrotated for each run ensuring continual efficacy across multiplespecies. The positive control samples from each tagging andamplification run are carried forward with the accompanying patientsamples and analyzed to ensure amplification through reporting generatesthe properly identified bacterium. Lastly, the resulting DNA is purifiedand again analyzed for purity and concentration prior to entering intothe sequencing protocols.

Next Generation DNA Sequencing—The sequencing reactions are preferablymonitored and filtered by several overlapping control procedures at boththe analysis and sequencing level. In certain implementations, tirst,the DNA fragments are linked to Ion Sphere Particles (ISPs) using acontrolled concentration to yield the highest resulting monoclonalISP/DNA population. The efficiency of labeling the ISPs may be assayedusing fluorescent probes whereby the ratios of leading and trailingsequences are measured and the ratios compared. In some aspects, initiallabeling must surpass about 10% prior to ISP enrichment. Enrichmentconsistently raises the ISP labeled monoclonal ISP level to greater thanabout 80%, thus ensuring sufficient DNA reads for proper analysis. Inaddition to controlling for the proper template and ISP assembly thesequencing reaction itself must be controlled. The semiconductor chip isautomatically tested by the system hardware to ensure this consumable isworking properly. Next, the sequencing reaction chemistry is assayed forperformance by the addition of control ISPs into the generated DNAlibrary. Problems with sequencing efficiency, noise, chemistry, orcontamination may be determined by observing the results from thecontrol ISPs. Finally, the chip loading and performance is analyzed bythe end of the run to identify any problems resulting from any of thepreceding preparation steps. The resulting quality and number ofsequence reads should preferably surpass expected parameters to beacceptable for analysis depending on the semiconductor chip sizeselected for the test run.

Bioinformatics Analysis—In certain implementations, the bioinformaticsanalysis is entirely computer executed with minimal human input orguidance, thus minimizing operator induced errors during the complexmathematical analysis of the resulting DNA sequence information.Resulting sequence reads that do not meet specific quality requirementsare preferably removed prior to analysis. Subsequent DNA sequences maybe identified independently using internationally curated databases andthe closes matches are selected. Depending on the resulting strength ofthe identification the best match for each sequence is recorded andcollated. The top result matches can meet additional quality metricsprior to being accepted as legitimate results. Furthermore, non-targetDNA sequences such as human contaminants can be screened out. Finally,the most significant and highest probability results can be presentedfor report building. Using these methods the genus can be correctlyidentified greater than about 60%, about 65%, about 70%, about 75%,about 80%, about 85%, about 90%, or about 95% of the time, while thespecific species may be correctly identified greater than about 20%,about 25%, about 30%, about 35%, about 40%, about 45%, about 50%, about55% about 60%, about 65%, about 70%, about 75%, about 80%, about 85%,about 90%, or about 95% of the time. Treatment recommendations may bepresented based on literature searches across the identified genusand/or species. Samples that fail to meet these requirements can berejected from analysis as, for example, a “No Significant SequencesDetected” result.

Result Report Building—Lastly, both a sequencing technician and theLaboratory Director may review the resulting data prior to resultreporting. Reports can be scrutinized for evidence of contamination,carryover, or failure of control parameters. Once these criteria aremet, the reports may be released to physicians or healthcare providersas, for example, a password protected PDF document.

System Validity

In addition to run-to-run performance controls listed above thedisclosed system and methods have undergone significant validation foridentification of naturally occurring and synthetic bacterialpopulations in a variety of sample types. For each pooled patient DNAlibrary a known microorganism slated for identification can be includedand the assay can be partially perpetually validated with theappropriate identification of the included positive control species. Thesource material for these cells or DNA may be provided from the AmericanType Culture Collection (ATCC) bioresource catalogue of well-studied andcharacterized standards. The selected control species include and rotatethrough known pathogens such as Borrelia burgdorferi, Mycoplasmaarthriditis, Eschericia coli, Bartonella henselae, Coxiella brunetii,and Bartonella bacilliformis. Additionally, the performance metrics forthe assay are selected to provide the most accurate picture of organismratios in a given sample. Simply, known combinations of organisms havebeen generated, and the best quality cutoffs to best replicate actualDNA contribution from mixed populations have been determined. Inaddition to single or combinatorial validation, a large number of realworld samples from a variety of sources have been processed. Theseinclude blood samples, tissue biopsies, synovial fluid, serum,cerebrospinal fluid, abscess material, and even dental infections. Asexpected the detected microbial populations reflect and are incongruence with previously published microbial populations appropriatefor the sample type; however, as also expected the identified ratios andspecific bacterial contributors vary from sample to sample with uniqueand identifying characteristics. Furthermore, dental abscesses have beenidentified having the main contributors from both the Streptococcus andStaphylococcus genera consistent with published expected results.

In some implementations, reports are distributed the day after asuccessful sequencing run and may include the following information.

Page 1

1. Patient, physician, and other pertinent test information is presentedat the top of the report for convenience in line with standardlaboratory reports.2. A bar graph displaying, for example, up to 6 of the top significantmicrobial species or microbials identified by the sequence analysis.This bar graph takes into account the strength of the identified result.DNA sequences of which a high probability match are found can beindicated as “Close Match” and can be represented as a solid bar, whileDNA sequences that are divergent but are the closest match to theorganism can be indicated as a “Potential Novel” and can be represented,for example, as a hatched bar on the graph. The relative percentcontribution is indicated underneath the bar graph for easy reference.3. A table of, for example, up to 6 of the top significant identifiedspecies including Genus specific treatments (e.g., antibiotics,antifungals, antivirals, or antiprotozoals) and any noted treatmentresistance for organisms in that Genus. It is important to note thatthese are not drug sensitivities derived from sequence information, butliterature derived suggestions as to what therapies show efficacy invivo or in vitro. Furthermore, treatments for the Genus may also show upin the noted resistance column, as the results are not mutuallyexclusive.4. A following Notes section can include performance characteristics ofthis assay both general and specific to the submitted sample.

Page 2+

5. The first section on Page 2 can include a complete listing of the allof the significant identified microbes including total sequence countsand percentages in addition to “Close Match” and “Potential Novel”counts and percentages. These may exceed the total of 6 organismspresented in the bar graph on Page 1.6. Finally detailed treatment susceptibility with references can belisted for each identified Genus and can be ordered in the order ofcontribution to the sample. This allows for easy reference to confirm orobtain detailed information about previous literature studying thesusceptibility of various bacterial Genera. This section may extend forseveral pages of detailed reference information.

In certain aspects, the present disclosure provides kits for theidentifying a plurality of microorganisms in a biological sample.Exemplary kits includes a) at least one forward primer comprising anadapter sequence and a priming sequence, for a target sequence, whereinthe target sequence comprises a sequence from a characteristic genesequence; and b) at least one reverse primer.

The kits may be used with an ion semiconductor sequencing platform. Thekits may comprise any of the primers disclosed herein, for example butlimited to, a forward primer comprising a barcode, a barcode adapter,and a target sequence comprising a sequence from the 16S rRNA gene. Thekit may also comprise nucleotides, buffers and/or a DNA polymerase.

Further exemplary embodiments of the disclosure provide systems andmethods for characterizing one or more microorganisms that may beutilized on a traditional or mobile computerized interfaces or networkcapable of providing the disclosed processing, querying, and displayingfunctionalities. Various examples of the disclosed systems and methodsmay be carried out through the use of one or more computers, processors,servers, databases, and the like. Various examples disclosed hereinprovide highly efficient computerized systems and methods forcharacterizing one or more microorganisms or DNA fragments thereof, suchas for example, pathogenic microorganisms in an efficient and timelymanner, such that the systems and methods are suitable for use inclinical settings. Exemplary systems and methods can also providetreatment and/or treatment sensitivity information related to the one ormore identified microorganism, such that a care provider can use suchinformation. FIG. 12 illustrates a system 100 in accordance withexemplary embodiments of the disclosure. As illustrated, system 100includes a computer 102, which can be connected to a network 104. System100 can also include one or more databases 106-110, which may form partof one or more servers, such as servers 112-116. Although illustrated aspart of separate servers, databases 106-110 can form part of the sameserver or part of a computer, such as computer 102 or another computer.

Computer 102 can include any suitable devices that performs the computerfunctions noted below. For example, computer 102 can be or include adesktop computer, notebook computer, workstation, network computer,personal data assistant, minicomputer, mainframe computer, server,supercomputer, mobile device, awearable computer, a sequencing (e.g.,DNA sequencing) device, or other device having suitable computingcapabilities.

Network 104 can be or include a local area network (LAN), a wide areanetwork, a personal area network, a campus area network, a metropolitanarea network, a global area network, or the like. Network 104 can becoupled to one or more computers 102, servers 112-116, other networks,and/or other devices using an Ethernet connection, other wiredconnections, a WiFi interface, other wireless interfaces, or othersuitable connection.

Servers 112-116 can include any suitable computing device, includingdevices described above in connection with computer 102. Similarly,databases 106-110 can include any suitable database, such as thosedescribed in more detail below.

FIG. 13 illustrates a method 200 of characterizing one or moremicroorganisms in accordance with various examples of the disclosure.Method 200 includes the steps of selecting, by a computer, a digitalfile comprising one or more digital DNA sequences, wherein each of theone or more digital DNA sequences corresponds to a microorganism to becharacterized (step 202); segmenting, by the computer, each of the oneor more digital DNA sequences into one or more first portions (step204); performing, by the computer, a set of alignments by comparing theone or more first portions to information stored in a first database(step 206); determining, by the computer, sequence portions from amongthe one or more first portions that have an alignment match to theinformation stored in the first database (step 208); optionally furthersegmenting, by the computer, each of the one or more digital DNAsequences into one or more second portions (step 210); performing, bythe computer, a set of alignments by comparing the one or more firstportions or the one or more second portions to information stored in asecond database (step 212); determining, by the computer, sequenceportions from among the one or more first portions or the one or moresecond portions that have an alignment match to the information storedin the second database (step 214); and characterizing one or moremicroorganisms or DNA fragments thereof based on the alignment match tothe information stored in one or more of the first database and thesecond database (step 216). Each of the steps can be performed using,for example, computer 102 of system 100.

In accordance with some examples of these embodiments, method 200 mayalso include a step of automatically detecting a sequence run prior tostep 202. FIG. 14 illustrates an exemplary sequence run and detectionprocess 300 suitable for use with method 200 and for method 400,described below. In a situation in which a genetic sequencing run is inprogress, an in-progress run may be detected—e.g., by a computer (step302). In response to the detection, the computer may query, for example,a server (e.g., on of servers 112-116) or other computing device onwhich the sequencing process is occurring to verify completion of thesequencing run (step 304). While it is contemplated that any appropriatefile format may be used, in some implementations, the processed sequencefile may optionally be converted from one format to another (step 306).For example, an original file may be in a BAM format which can then beconverted to a FASTQ file format for further processing and/or datamanipulation. Alternatively, the processed sequence file may be in anSFF, FASTQ, or any other appropriate format that is convertible to aFASTQ file format. The file(s) can then be downloaded or otherwisetransferred to a computing device for further analysis (step 308), suchas for use with method 200. Alternatively, method 200 can employ asequence file that is, e.g., in FASTQ or other appropriate format from apreviously completed sequencing run. Regardless of whether a file ismanually selected by a user or automatically detected by the computingdevice in accordance with FIG. 3, an implementation of the method maythen convert the FASTQ or other file format into one or more easilyusable FASTA formatted or other appropriately formatted files,illustrated as step 310 in FIG. 3. During step 310, during the fileconversion, the sequencing device type and/or the microorganism type canbe detected. This allows the method (e.g., method 200 or 400) toautomatically process the sequences based on an incoming data (e.g., fora sequencer type) and/or microorganism type.

Referring again to FIG. 13, during step 202, a digital file comprisingone or more digital DNA sequences is selected. The digital file caninclude a plurality of DNA sequences from the one or more files (e.g.,FASTA files) that can comprise a predetermined number of base pairs (bp)or otherwise have a predetermined length. In some implementations, 100bp may be a preferred number of base pairs at which to set thisselection threshold, however, any other number of base pairs that allowsfor adequate processing and elimination of sequence portions that areunlikely to lead to meaningful analysis may also be selected. Forexample, greater than or equal to 50 bp, 100 bp, or 150 bp may be used.

During step 204, the selected DNA sequence file(s) are segmented intoone or more first portions, which may be of equal size or length. Whileany number of (e.g., equal) portions may be used, in someimplementations, it may be desirable to match the number of portions tothe number of processing cores to be used by a system for processing.For example, when using an analysis computer that has 32 cores, it maybe desirable to use 30 of those cores for processing while keeping theremaining two cores in reserve for data management and other processingfunctions. By way of particular example, it may then be preferable todivide the (e.g., FASTA) sequence file into 30 equal portions, such thatone portion of the file may be processed by each desired processingcore.

Once the division of one or more digital DNA sequences into one or morefirst portions is complete, a set of alignments is performed bycomparing the one or more first portions to information stored in afirst database (step 206). The alignments can be performed using avariety of techniques, including Basic Local Alignment Search Tool(BLAST), OTU, G-BLASTN, mpiBLAST, BLASTX, PAUDA, USEARCH, LAST, BLAT, orother suitable technique.

The first database (e.g., one of databases 106-110) can include adatabase that includes nucleic acid information (e.g., DNA and/or RNAinformation) corresponding to one or more types of microorganism—e.g.,bacteria, viruses, protozoa, or fungi. By way of examples, the firstdatabase can include a bacterial nucleic acid database, such as an 16SMicrobial DNA Database.

By way of particular examples, step 206 can include performing a set ofalignments using BLAST by comparing each of the sequence file portionsto a say a DNA database of 16S rRNA Microbial sequences (Bacteria andArchaea) (hereinafter referred to as “16S”) database, such as theNational Center for Biotechnology Information (NCBI) 16S database.

The alignments may in some implementations occur substantiallysimultaneously. It may also be preferable to perform the alignmentsduring step 206 using a relatively small comparison window (e.g., 10 bpor 11 bp) as the first database may be relatively small and thus, theprocessing time does not become prohibitive even with relatively smallcomparison windows. Although not illustrated, method 200 can includecollating the aggregate results and eliminating any duplicates present.This may be done, for example, when the alignments are complete at step206.

During step 208, a computer determines sequence portions from among theone or more first portions that have an alignment match to theinformation stored in the first database. The step of determining may bebased on a predetermined criteria or tolerance for a match.

During step 210, each of the one or more digital DNA sequences from step202 are optionally further segmented into one or more second portions.Step 210 can be performed in substantially the same way as step 204.During this optional step, the sequence files can be divided into asecond plurality of sequence portions, which may be of equal size and/orthe number of portions may be determined by a preferred number ofprocessing cores to be used. In accordance with some exemplaryembodiments, the second portions differ or are exclusive of the firstportions.

During step 212, a set of alignments by comparing the one or more firstportions or the one or more second portions (if optional step 210 isperformed) to information stored in a second database is performed. Step212 is similar to step 206, except either first portions or secondportions are compared to a second database.

The second database may be relatively large relative to the firstdatabase. As such, to reduce processing time, it may be desirable to usea comparison window that is relatively large (e.g., 65 bp, 100 bp, orthe like), especially for a first run of step 212. The second databasecan be or include, for example, a comprehensive nucleic acids database,such as a comprehensive DNA database, a comprehensive RNA database, aeukaryotic DNA database, an NT database, a fungi DNA database, aprotozoa DNA database, a comprehensive bacterial nuecleic acidsdatabase, or a viral nucleic acids database.

As shown in FIG. 13, steps 210-214 can be repeated—e.g., in an iterativemanner, wherein a comparison window for determining a match decreases asthe number (n) of runs increases. For example, the initial comparisonwindow size can start at 65 bp, and decrease to 40 bp, 25 bp, 10 bp withsubsequent runs.

The alignment results from step 212 can be collated and any duplicatesremoved. The results can then be checked to determine if all of thesequence file portions were aligned through the running of thealignments.

Step 214 can be performed in a manner similar to or the same as step208. If the alignments performed on the second portions are done using alarge comparison window, the results of these alignments may not producea match between the sequence of the file portion and the seconddatabase, due to the low level of stringency. If there are any of thesequence file portions for which the alignment did not identify a matchwithin the second database, a size of a comparison window can beadjusted (e.g., automatically) to increase the stringency—i.e., decreasea size of a comparison window—of a subsequent alignment. The previouslyunidentified sequence portions are then passed iteratively back into thefile segmentation stage 210 where they may then be segmented into anydesired number of (e.g., equally) sized sequence portions and alignmentsare then run for each of the portions. These steps may be iterativelyrepeated and the stringency increased (comparison window size decreased)each time step 212 is performed and fails to produce a resulting matchin step 214. By starting with a lower stringency (e.g., large comparisonwindow) and increasing the stringency (e.g., decreasing the comparisonwindow)—e.g., in a manner that is directly proportional to the number oftimes which a portion of the sequence has passed through an alignmentand failed to find a match, significant processing time may be saved.For example, beginning with a low stringency having a comparison windowof 65 bp and then iteratively increasing the stringency by decreasingthe comparison window to, for example, 40 bp, 25 bp, and finally 10 bprather than simply running all of the second database alignments with acomparison window of 10 bp from the start may reduce processing time bymany hours or even days. The method may also utilize a maximumstringency (minimum comparison window size) setting in which anyleftover sequence portions that have not resulted in a second databasematch after having been aligned at the highest designated stringencylevel are discarded to prevent unnecessary processing from continuing.

Table 1 below illustrates the effect of window size on speed and rate atwhich sequences are characterized in addition to the ratio ofcontaminating human sequences vs the target microbial sequences.

TABLE 1 Comparison Human/ Window % Time Non- Size Recovery (min) HumanNonHuman Seq/Min %/Min Human 200 13.4% 2.7 11500 57 4344.7 5.1% 201.8150 35.7% 4.4 30538 148 7022.0 8.2% 206.3 100 63.5% 4.7 54231 31111679.2 13.6% 174.4  90 71.9% 4.7 61433 376 13039.9 15.2% 163.4  8079.4% 5.3 67848 422 12832.7 14.9% 160.8  75 85.2% 4.7 72811 466 15524.818.1% 156.2  70 88.6% 4.8 75222 920 15896.0 18.5% 81.8  65 90.5% 4.976724 1026 15932.4 18.5% 74.8  64 90.8% 5.0 76991 1041 15606.4 18.2%74.0  63 91.4% 5.4 77481 1064 14681.3 17.1% 72.8  62 91.9% 5.0 779171096 15834.3 18.4% 71.1  60 92.6% 5.8 78472 1146 13822.6 16.1% 68.5  5096.0% 5.8 81078 1460 14304.7 16.6% 55.5  40 98.6% 8.8 82945 1849 9592.111.2% 44.9  25 99.9% 48.7 83349 2508 1763.7 2.1% 33.2

At step 216, one or more microorganisms are characterized. Thecharacterization can include identifying the one or more microorganismsor finding a close match of an unknown microorganism to a known orunknown microorganism in a database.

Exemplary methods can also include a comparison of results from the twoalignments determination steps 208 and 214. For example, once collationand removal of duplicate results has been accomplished for both thefirst database alignments results and the second database (optionallyiteratively performed) aligned results, the results of the two databasesalignments can be compared. In some implementations of the method, thefirst database alignment results may first be examined to determine ifthere are any complete, or 100%, matches. If so, these are assumed to becorrectly identified microorganisms due to their high degree of matchingand can be placed into a first list. The first database results can thenre-analyzed to find matches having a slightly lesser degree ofcompleteness, but for which there is still a reasonably high probabilitythat the microorganism has been correctly identified and these resultsare also added to the first list. For example, the matches can be 100%,98%, 97%, 95%, or 90%. For the remaining first database results thatfall below the predetermined threshold of reliability for the results tobecome a member of the first list, a comparison can made with thecorresponding second database results for each particular sequenceportion to determine whether the second database result (e.g., a matchduring step 214) or the first database result (from step 208) provides acloser match. In some implementation, this may be accomplished bycomparing one or more variables, such as for example, one or more of apercentage identity and sequence E-value, to determine which of the twodatabase alignments result in the closest match. Once it is determinedwhich is the closer match, the results can further analyzed tocharacterize and/or identify any of the closest matches that do not fallabove a predetermined threshold (e.g., 100%, 98%, 97%, 95%, or 90%) ofcertainty and these results may be categorized as results that do notcorrespond with the characterized microorganism(s).

A quality of the results of comparisons of matches from steps 208 and214 can be checked by limiting the analysis to sequence portions thathave a predetermined length. For example, either a minimum threshold forsequence length could be set such as, for example, a minimum sequencelength of 100 bp, or the results may be limited such that only thoseabove which fall into a certain percentage of the longest sequences, forexample, the top 100%, 50%, 30%, 20%, 15%, or 10% of all run sequencelengths may be selected on which to base the remaining analysis. By wayof one example, the top 8.6% of sequence lengths can be used. Theresults can then be tabulated to determine how many matches correspondto each characterized or identified microorganism and any regioninformation can also be tabulated to determine the number of matches foreach region analyzed.

The system can then query a database of treatment information that maycontain information such as the treatment (e.g., antibiotic, antiviral,antifungal, antiprotozoal) treatment and sensitivity and/or therapyresistance of the treatment(s) corresponding to each identifiedmicroorganism and the retrieved information may then be used to generatea final report. As shown in FIGS. 16-17, the output of the final reportmay display information such as, but not limited to: patientinformation, medical professional information, sample type, collectiondate, graphical or numerical data relating to one or more characterizedor identified microorganisms, a percentage or other numerical indicatorof contribution amount of each identified microorganism, a quantitativeindicator for a match (e.g., an E-value or % Identity), a description ofidentified and/or unidentified (novel) microorganisms, and/or treatmentsensitivity and/or therapy resistance information.

It may be advantageous to implement the disclosed system and methods ina language or other format that is compatible with a sequencingplatform, such as an ionssemiconductor sequencing platform—e.g., an anIonTorent Server or an Illumina sequencer, as this may provide addedefficiencies to the overall implementation.

Turning now to FIG. 15, a method 400 of automatically characterizing oneor more microorganisms is illustrated. Method 400 is similar to method200, except method 400 includes a step of detecting a sequence run thatgenerates a digital DNA sequence of one or more microorganism (step 402)and does not necessarily, but can, include a performing a set ofalignments by comparing the one or more sequence portions to informationstored in a second database.

In the illustrated example, method 400 includes the steps of detecting asequence run that generates a digital DNA sequence of one or moremicroorganisms (step 402); selecting, by a computer, a digital filecomprising one or more digital DNA sequences, wherein each of the one ormore digital DNA sequences corresponds to a microorganism to becharacterized (step 404); segmenting, by the computer, each of the oneor more digital DNA sequences into one or more portions (step 406);performing, by the computer, a set of alignments by comparing the one ormore portions to information stored in one or more databases (step 408);determining, by the computer, sequence portions from among the one ormore portions that have an alignment match to the information stored inthe one or more databases (step 410); and characterizing one or moremicroorganisms or DNA fragments thereof based on the alignment match(step 412).

Step 402 includes automatically detecting a sequence run that generatesa digital DNA sequence of one or more microorganisms. This can be doneas described above in connection with process 300. Steps 404-412 can bethe same or similar to steps 202-208 and 216 of method 200.

Method 400 can also include steps of optionally further segmenting, bythe computer, each of the one or more digital DNA sequences into one ormore second portions (wherein the portions noted above become firstportions); performing, by the computer, a set of alignments by comparingthe one or more first portions or the one or more second portions toinformation stored in a database (e.g., a second database); anddetermining, by the computer, sequence portions from among the one ormore first portions or the one or more second portions that have analignment match to the information stored in a database (e.g., thesecond database). Similar to method 200, these steps can be iterativelyrepeated with a comparison window decreasing in size with each run.Additional steps noted above in connection with method 200 can also beincludes in method 400.

In accordance with various embodiments of the disclosure, method 200 ormethod 400 can be performed on a computer on a local network. Byperforming the processing functions of the disclosed systems or methodslocally within the system, an Internet connection is not needed tosustain the processing. This offers additional security and reducesnetworking requirements. Implementations of the disclosed system andmethod are intended to integrate with existing and future NextGeneration Sequencing software platforms such as, for example, Illumina®software applications such as Illumina MiSeq® and Illumina HiSeq®;LifeTechnologies Proton®; LifeTechnologies Personal Genome Machine, andPacBioRS II NGS sequencing systems.

Exemplary methods of the present disclosure described above may beimplemented as one or more software processes executable by one or moreprocessors and/or one or more firmware applications. The processesand/or firmware are configured to operate on one or more general purposemicroprocessors or controllers, a field programmable gate array (FPGA),an application specific integrated circuit (ASIC), or other hardwarecapable of performing the actions describe above. In an exemplaryembodiment of the present disclosure, software processes are executed bya CPU in order to perform the actions of the present disclosure.Additionally, the present disclosure is not described with reference toany particular programming language. It will be appreciated that avariety of programming languages may be used to implement the teachingsof the disclosure as described herein.

Any of the methods herein may be employed with any form of memory deviceincluding all forms of sequential, pseudo-random, and random accessstorage devices. Storage devices as known within the current art includeall forms of random access memory, magnetic and optical tape, magneticand optical disks, along with various other forms of solid-state massstorage devices. The current disclosure applies to all forms and mannersof memory devices including, but not limited to, storage devicesutilizing magnetic, optical, and chemical techniques, or any combinationthereof.

This disclosure is further illustrated by the following additionalexamples that should not be construed as limiting. It can be appreciatedthat many changes can be made to the specific embodiments which aredisclosed and still obtain a like or similar result without departingfrom the spirit and scope of the disclosure.

EXAMPLES Example 1 General DNA Extraction Procedures

Tissues, fluids, other biopsy material, environmental, or industrialmaterial that is suspected of containing bacterial cells can beextracted using one of three main methods:

Bone or Tough Tissue Preparation

-   -   1) ˜200 mg of bone or tissue is placed in a sterile 50 mL        conical tube and 5 mL of molecular grade water is added to the        sample.    -   2) The tissue is sonicated in 5-10 second bursts for a minimum        of 5 minutes using a sterile sonicator probe at 10-14 watts.    -   3) 200 μL of supernatant and any remaining bone/tissue fragments        are transferred to a sterile 2 mL screw cap tube and 50-100 μL        of 1 mm uneven stainless steel beads, 200 μL of Qiagen Buffer        AL, and 20 μL of Proteinase K is added to the sample.    -   4) The tube is then processed using a percussion based bead        homogenizer for 5 minutes at medium speed.

5) 600 μL of the resulting supernatant is run through an inert filtercolumn to remove beads.

-   -   6) 200 μL of 100% Ethanol is added to the sample.    -   7) From here the remaining steps are carried out as described in        the Qiagen QIAamp DNA Blood Mini Kit protocol.    -   8) Final DNA is eluted in 30 μL.    -   9) Concentration of the extracted DNA is determined by NanoDrop        analysis (Thermo Scientific, Wilmington, Del.) of 4 μL.

Soft Tissue Preparation

-   -   1) 200 mg of soft tissue and 200 μL of molecular grade water is        transferred to a sterile 2 mL screw cap tube and 50-100 μL of 1        mm glass beads, 200 μL of Qiagen Buffer AL, and 20 μL of        Proteinase K is added to the sample.    -   2) The tube is then processed using a percussion based bead        homogenizer for 5 minutes at medium speed.    -   3) ˜600 μL of the resulting supernatant is run through an inert        filter column to remove beads.    -   4) 200 μL of 100% Ethanol is added to the sample.    -   5) From here the remaining steps are carried out as described in        the Qiagen QIAamp DNA Blood Mini Kit protocol.    -   6) Final DNA is eluted in 30 μL.    -   7) Concentration of the extracted DNA is determined by NanoDrop        analysis (Thermo Scientific, Wilmington, Del.) of 4 μL.

Fluid Preparation

-   -   1) 200 μL of blood or fluid is transferred to a sterile 2 mL        screw cap tube and 50-100 μL of 1 mm glass beads, 200 μL of        Qiagen Buffer AL, and 20 μL of Proteinase K is added to the        sample.    -   2) The tube is then processed using a percussion based bead        homogenizer for 5 minutes at medium speed.    -   3) ˜400 μL of the resulting supernatant is run through an inert        filter column to remove beads.    -   4) 200 μL of 100% Ethanol is added to the sample.    -   5) From here the remaining steps are carried out as described in        the Qiagen QIAamp DNA Blood Mini Kit protocol.    -   6) Final DNA is eluted in 30 μL.    -   7) Concentration of the extracted DNA is determined by NanoDrop        analysis (Thermo Scientific, Wilmington, Del.) of 4 μL.

Example 2 DNA Purification from Tissues with the QIAamp® DNA Mini Kit

DNA can be purified from tissues using the QIAamp® DNA Mini Kit (QIAGEN,Germantown, Md.).

Important points before starting:

-   -   All centrifugation steps can be carried out at room temperature        (˜15-25° C.).    -   Use carrier DNA if the sample contains <10,000 genome        equivalents.    -   Avoid repeated freezing and thawing of stored samples, since        this leads to reduced DNA size.

Transcriptionally active tissues, such as liver and kidney, contain highlevels of RNA which will copurify with genomic DNA. RNA may inhibit somedownstream enzymatic reactions, but will not inhibit PCR. If RNA-freegenomic DNA is required, include an RNase A digest.

Things to do before starting:

-   -   Equilibrate the sample to room temperature (˜15-25° C.).    -   Heat 2 water baths or heating blocks: one to 56° C. for use in        step 3, and one to 70° C. for use in step 5.    -   Equilibrate Buffer AE or distilled water to room temperature for        elution in step 11.    -   Ensure that Buffers AW1 and AW2 have been prepared.    -   If a precipitate has formed in Buffer ATL or Buffer AL, dissolve        by incubating at 56° C.

Exemplary Procedure

1. Excise the tissue sample or remove it from storage. Determine theamount of tissue. Do not use more than 25 mg (10 mg spleen). Weighingtissue is the most accurate way to determine the amount. If DNA isprepared from spleen tissue, no more than 10 mg should be used. Theyield of DNA will depend on both the amount and the type of tissueprocessed. 1 mg of tissue will yield approximately 0.2-1.2 μg of DNA.

2. Cut up (step 2a), grind (step 2b), or mechanically disrupt (step 2c)the tissue sample. The QIAamp procedure requires no mechanicaldisruption of the tissue sample, but lysis time will be reduced if thesample is ground in liquid nitrogen (step 2b) or mechanicallyhomogenized (step 2c) in advance.

2a. Cut up to 25 mg of tissue (up to 10 mg spleen) into small pieces.Place in a 1.5 ml microcentrifuge tube, and add 180 μl of Buffer ATL.Proceed with step 3. It is important to cut the tissue into small piecesto decrease lysis time. 2 ml microcentrifuge tubes may be better suitedfor lysis.

2b. Place up to 25 mg of tissue (10 mg spleen) in liquid nitrogen, andgrind thoroughly with a mortar and pestle. Decant tissue powder andliquid nitrogen into 1.5 ml microcentrifuge tube. Allow the liquidnitrogen to evaporate, but do not allow the tissue to thaw, and add 180μl of Buffer ATL. Proceed with step 3.

2c. Add up to 25 mg of tissue (10 mg spleen) to a 1.5 ml microcentrifugetube containing no more than 80 μl PBS. Homogenize the sample using theTissueRuptor or equivalent rotor-stator homogenizer. Add 100 μl BufferATL, and proceed with step 3. Some tissues require undiluted Buffer ATLfor complete lysis. In this case, grinding in liquid nitrogen isrecommended. Samples cannot be homogenized directly in Buffer ATL, whichcontains detergent.

3. Add 20 μl proteinase K, mix by vortexing, and incubate at 56° C.until the tissue is completely lysed. Vortex occasionally duringincubation to disperse the sample, or place in a shaking water bath oron a rocking platform. Note: Proteinase K can be used. QIAGEN Proteasehas reduced activity in the presence of Buffer ATL. Lysis time variesdepending on the type of tissue processed. Lysis is usually complete in1-3 h. Lysis overnight is possible and does not influence thepreparation. In order to ensure efficient lysis, a shaking water bath ora rocking platform can be used. If not available, vortexing 2-3 timesper hour during incubation is recommended.

4. Briefly centrifuge the 1.5 ml microcentrifuge tube to remove dropsfrom the inside of the lid.

5. If RNA-free genomic DNA is desired, follow step 5a. Otherwise, followstep 5b. Transcriptionally active tissues, such as liver and kidney,contain high levels of RNA which will copurify with genomic DNA. RNA mayinhibit some downstream enzymatic reactions, but will not inhibit PCR.

5a. First add 4 μl RNase A (100 mg/ml), mix by pulse-vortexing for 15 s,and incubate for 2 min at room temperature. Briefly centrifuge the 1.5ml microcentrifuge tube to remove drops from inside the lid beforeadding 200 μl Buffer AL to the sample. Mix again by pulse-vortexing for15 s, and incubate at 70° C. for 10 min. Briefly centrifuge the 1.5 mlmicrocentrifuge tube to remove drops from inside the lid. It isdesirable that the sample and Buffer AL are mixed thoroughly to yield ahomogeneous solution. A white precipitate may form on addition of BufferAL. In most cases the precipitate will dissolve during incubation at 70°C. The precipitate does not interfere with the QIAamp procedure or withany subsequent application.

5b. Add 200 μl Buffer AL to the sample, mix by pulse-vortexing for 15 s,and incubate at 70° C. for 10 min. Briefly centrifuge the 1.5 mlmicrocentrifuge tube to remove drops from inside the lid. It isdesirable that the sample and Buffer AL are mixed thoroughly to yield ahomogeneous solution. A white precipitate may form on addition of BufferAL, which in most cases will dissolve during incubation at 70° C. Theprecipitate does not interfere with the QIAamp procedure or with anysubsequent application.

6. Add 200 μl ethanol (96-100%) to the sample, and mix bypulse-vortexing for 15 s. After mixing, briefly centrifuge the 1.5 mlmicrocentrifuge tube to remove drops from inside the lid. It isessential that the sample, Buffer AL, and the ethanol are mixedthoroughly to yield a homogeneous solution. A white precipitate may formon addition of ethanol. It is desirable to apply all of the precipitateto the QIAamp Mini spin column. This precipitate does not interfere withthe QIAamp procedure or with any subsequent application. Use alcoholsother than ethanol may result in reduced yields.

7. Carefully apply the mixture from step 6 (including the precipitate)to the QIAamp Mini spin column (in a 2 ml collection tube) withoutwetting the rim. Close the cap, and centrifuge at 6000×g (8000 rpm) for1 min. Place the QIAamp Mini spin column in a clean 2 ml collectiontube, and discard the tube containing the filtrate. Close each spincolumn to avoid aerosol formation during centrifugation. It is desirableto apply all of the precipitate to the QIAamp Mini spin column.Centrifugation is performed at 6000×g (8000 rpm) in order to reducenoise. Centrifugation at full speed will not affect the yield or purityof the DNA. If the solution has not completely passed through themembrane, centrifuge again at a higher speed until all the solution haspassed through.

8. Carefully open the QIAamp Mini spin column and add 500 μl Buffer AW1without wetting the rim. Close the cap, and centrifuge at 6000×g (8000rpm) for 1 min. Place the QIAamp Mini spin column in a clean 2 mlcollection tube, and discard the collection tube containing thefiltrate.

9. Carefully open the QIAamp Mini spin column and add 500 μl Buffer AW2without wetting the rim. Close the cap and centrifuge at full speed(20,000×g; 14,000 rpm) for 3 min.

10. Recommended: Place the QIAamp Mini spin column in a new 2 mlcollection tube and discard the old collection tube with the filtrate.Centrifuge at full speed for 1 min. This step helps to eliminate thechance of possible Buffer AW2 carryover.

11. Place the QIAamp Mini spin column in a clean 1.5 ml microcentrifugetube, and discard the collection tube containing the filtrate. Carefullyopen the QIAamp Mini spin column and add 200 μl Buffer AE or distilledwater. Incubate at room temperature for 1 min, and then centrifuge at6000×g (8000 rpm) for 1 min.

12. Repeat step 11. A 5 min incubation of the QIAamp Mini spin columnloaded with Buffer AE or water, before centrifugation, generallyincreases DNA yield. A third elution step with a further 200 μl BufferAE will increase yields by up to 15%. Volumes of more than 200 μl shouldnot be eluted into a 1.5 ml microcentrifuge tube because the spin columnwill come into contact with the eluate, leading to possible aerosolformation during centrifugation. Elution with volumes of less than 200μl increases the final DNA concentration in the eluate significantly,but slightly reduces the overall DNA yield. Eluting with 4×100 μlinstead of 2×200 μl does not increase elution efficiency. For long-termstorage of DNA, eluting in Buffer AE and placing at ˜20° C. isrecommended, since DNA stored in water is subject to acid hydrolysis.Yields of DNA can depend both on the amount and the type of tissueprocessed. 25 mg of tissue can yield approximately 10-30 μg of DNA in400 μl of water (25-75 ng/μl), with an A₂₆₀/A₂₈₀ ratio of 1.7-1.9.

Example 3 DNA Purification from Blood with the QIAamp® DNA Mini Kit

DNA can be purified from blood using the QIAamp® DNA Mini Kit (QIAGEN,Germantown, Md.).

This protocol can be for purification of total (genomic, mitochondrial,and viral) DNA from whole blood, plasma, serum, buffy coat, lymphocytes,and body fluids using a microcentrifuge.

Important points before starting:

-   -   All centrifugation steps are carried out at room temperature        (˜15-25° C.).    -   Use carrier DNA if the sample contains <10,000 genome        equivalents.    -   200 μl of whole blood yields 3-12 μg of DNA. Preparation of        buffy coat is recommended if a higher yield is desired.

Things to do before starting:

-   -   Equilibrate samples to room temperature.    -   Heat a water bath or heating block to 56° C. for use in step 4.    -   Equilibrate Buffer AE or distilled water to room temperature for        elution in step 11.    -   Ensure that Buffer AW1, Buffer AW2, and QIAGEN Protease have        been prepared.    -   If a precipitate has formed in Buffer AL, dissolve by incubating        at 56° C.

Exemplary Procedure

1. Pipet 20 μl QIAGEN Protease (or proteinase K) into the bottom of a1.5 ml microcentrifuge tube.

2. Add 200 μl sample to the microcentrifuge tube. Use up to 200 μl wholeblood, plasma, serum, buffy coat, or body fluids, or up to 5×106lymphocytes in 200 μl PBS. If the sample volume is less than 200 μl, addthe appropriate volume of PBS. QIAamp Mini spin columns copurify RNA andDNA when both are present in the sample. RNA may inhibit some downstreamenzymatic reactions, but not PCR. If RNA-free genomic DNA is desired, 4μl of an RNase A stock solution (100 mg/ml) should be added to thesample before addition of Buffer AL. Note: It is possible to add QIAGENProtease (or proteinase K) to samples that have already been dispensedinto microcentrifuge tubes. In this case, it is desirable to ensureproper mixing after adding the enzyme.

3. Add 200 μl Buffer AL to the sample. Mix by pulse-vortexing for 15 s.In order to ensure efficient lysis, it is desirable that the sample andBuffer AL are mixed thoroughly to yield a homogeneous solution. If thesample volume is larger than 200 μL, increase the amount of QIAGENProtease (or proteinase K) and Buffer AL proportionally; for example, a400 μl sample will use 40 μl QIAGEN Protease (or proteinase K) and 400μl Buffer AL. If sample volumes larger than 400 μl are desired, use ofQIAamp DNA Blood Midi or Maxi Kits is recommended; these can process upto 2 ml or up to 10 ml of sample, respectively. Note: Do not add QIAGENProtease or proteinase K directly to Buffer AL.

4. Incubate at ˜56° C. for ˜10 min. DNA yield reaches a maximum afterlysis for ˜10 min at ˜56° C. Longer incubation times have may no effecton yield or quality of the purified DNA.

5. Briefly centrifuge the 1.5 ml microcentrifuge tube to remove dropsfrom the inside of the lid.

6. Add 200 μl ethanol (96-100%) to the sample, and mix again bypulse-vortexing for 15 s. After mixing, briefly centrifuge the 1.5 mlmicrocentrifuge tube to remove drops from the inside of the lid. If thesample volume is greater than 200 μl, increase the amount of ethanolproportionally; for example, a 400 μl sample can use 400 μl of ethanol.

7. Carefully apply the mixture from step 6 to the QIAamp Mini spincolumn (in a 2 ml collection tube) without wetting the rim. Close thecap, and centrifuge at 6000×g (8000 rpm) for 1 min. Place the QIAampMini spin column in a clean 2 ml collection tube, and discard the tubecontaining the filtrate. Close each spin column in order to avoidaerosol formation during centrifugation. Centrifugation is performed at6000×g (8000 rpm) in order to reduce noise. Centrifugation at full speedwill not affect the yield or purity of the DNA. If the lysate has notcompletely passed through the column after centrifugation, centrifugeagain at higher speed until the QIAamp Mini spin column is empty. Note:When preparing DNA from buffy coat or lymphocytes, centrifugation atfull speed is recommended to avoid clogging.

8. Carefully open the QIAamp Mini spin column and add 500 μl Buffer AW1without wetting the rim. Close the cap and centrifuge at 6000×g (8000rpm) for 1 min. Place the QIAamp Mini spin column in a clean 2 mlcollection tube, and discard the collection tube containing thefiltrate. It is not necessary to increase the volume of Buffer AW1 ifthe original sample volume is larger than 200 μl.

9. Carefully open the QIAamp Mini spin column and add 500 μl Buffer AW2without wetting the rim. Close the cap and centrifuge at full speed(20,000×g; 14,000 rpm) for 3 min.

10. Recommended: Place the QIAamp Mini spin column in a new 2 mlcollection tube and discard the old collection tube with the filtrate.Centrifuge at full speed for 1 min. This step helps to eliminate thechance of possible Buffer AW2 carryover.

11. Place the QIAamp Mini spin column in a clean 1.5 ml microcentrifugetube, and discard the collection tube containing the filtrate. Carefullyopen the QIAamp Mini spin column and add 200 μl Buffer AE or distilledwater. Incubate at room temperature (15-25° C.) for 1 min, and thencentrifuge at 6000×g (8000 rpm) for 1 min. Incubating the QIAamp Minispin column loaded with Buffer AE or water for 5 min at room temperaturebefore centrifugation generally increases DNA yield. A second elutionstep with a further 200 μl Buffer AE will increase yields by up to 15%.Volumes of more than 200 μl should not be eluted into a 1.5 mlmicrocentrifuge tube because the spin column will come into contact withthe eluate, leading to possible aerosol formation during centrifugation.Elution with volumes of less than 200 μl increases the final DNAconcentration in the eluate significantly, but slightly reduces theoverall DNA yield. For samples containing less than 1 μg of DNA, elutionin 50 μl Buffer AE or water is recommended. Eluting with 2×100 μlinstead of 1×200 μl does not increase elution efficiency. For long-termstorage of DNA, eluting in Buffer AE and storing at ˜20° C. isrecommended, since DNA stored in water is subject to acid hydrolysis. A200 μl sample of whole human blood (approximately 5×106 leukocytes/ml)typically yields 6 μg of DNA in 200 μl water (30 ng/μl) with anA260/A280 ratio of 1.7-1.9.

Example 4 Amplification and Barcoding of Extracted DNA

PCR amplification reactions are set up for two 16S regions per sample.Each sample is designated by its own DNA barcode. The followingreactions are generated for each sample including one positive and onenegative amplification control:

Region V1/2 Region V5/4 3.48 μL dH2O 3.48 μL dH2O 5.00 μL ENA 5.00 μLENA 0.26 μL A_BarcodeX_V1/2_F 0.26 μL A_BarcodeX_V5/4_F 0.26 μLP1_V1/2_R 0.26 μL P1_V5/4_R 1.00 μL Template DNA 1.00 μL Template DNA

Note that in the above PCR reaction mixtures that ENA are2′-O,4′-C-ethylene bridged nucleic acids; A_BarcodeX_V1/2_F andA_BarcodeX_V5/4_F are forward primers; and P1_V_(—)1/2_R and P1_V5/4_Rare reverse primers. The V1/2 primers are selected from Table 4, and theV5/4 primers are selected from Table 5.

TABLE 4 Examples of V1/2 Primers. Barcodes are underlined, and the 16SVariable Region Homology is in bold. Forward Primer (Primer A-Barcode1-V1/2) (SEQ ID NO: 35)CCATCTCATCCCTGCGTGTCTCCGACTCAGCTAAGGTAACGATAGAGTTTGATCCTGGCTCAG ForwardPrimer (Primer A-Barcode 2-V1/2) (SEQ ID NO: 36)CCATCTCATCCCTGCGTGTCTCCGACTCAGTAAGGAGAACGATAGAGTTTGATCCTGGCTCAG ForwardPrimer (Primer A-Barcode 3-V1/2) (SEQ ID NO: 37)CCATCTCATCCCTGCGTGTCTCCGACTCAGAAGAGGATTCGATAGAGTTTGATCCTGGCTCAG ForwardPrimer (Primer A-Barcode 4-V1/2) (SEQ ID NO: 38)CCATCTCATCCCTGCGTGTCTCCGACTCAGTACCAAGATCGATAGAGTTTGATCCTGGCTCAG ForwardPrimer (Primer A-Barcode 5-V1/2) (SEQ ID NO: 39)CCATCTCATCCCTGCGTGTCTCCGACTCAGCAGAAGGAACGATAGAGTTTGATCCTGGCTCAG ForwardPrimer (Primer A-Barcode 6-V1/2) (SEQ ID NO: 40)CCATCTCATCCCTGCGTGTCTCCGACTCAGCTGCAAGTTCGATAGAGTTTGATCCTGGCTCAG ForwardPrimer (Primer A-Barcode 7-V1/2) (SEQ ID NO: 41)CCATCTCATCCCTGCGTGTCTCCGACTCAGTTCGTGATTCGATAGAGTTTGATCCTGGCTCAG ForwardPrimer (Primer A-Barcode 8-V1/2) (SEQ ID NO: 42)CCATCTCATCCCTGCGTGTCTCCGACTCAGTTCCGATAACGATAGAGTTTGATCCTGGCTCAG ForwardPrimer (Primer A-Barcode 9-V1/2) (SEQ ID NO: 43)CCATCTCATCCCTGCGTGTCTCCGACTCAGTGAGCGGAACGATAGAGTTTGATCCTGGCTCAG ForwardPrimer (Primer A-Barcode 10-V1/2) (SEQ ID NO: 44)CCATCTCATCCCTGCGTGTCTCCGACTCAGCTGACCGAACGATAGAGTTTGATCCTGGCTCAG ForwardPrimer (Primer A-Barcode 11-V1/2) (SEQ ID NO: 45)CCATCTCATCCCTGCGTGTCTCCGACTCAGTCCTCGAATCGATAGAGTTTGATCCTGGCTCAG ForwardPrimer (Primer A-Barcode 12-V1/2) (SEQ ID NO: 46)CCATCTCATCCCTGCGTGTCTCCGACTCAGTAGGTGGTTCGATAGAGTTTGATCCTGGCTCAG ForwardPrimer (Primer A-Barcode 13-V1/2) (SEQ ID NO: 47)CCATCTCATCCCTGCGTGTCTCCGACTCAGTCTAACGGACGATAGAGTTTGATCCTGGCTCAG ForwardPrimer (Primer A-Barcode 14-V1/2) (SEQ ID NO: 48)CCATCTCATCCCTGCGTGTCTCCGACTCAGTTGGAGTGTCGATAGAGTTTGATCCTGGCTCAG ForwardPrimer (Primer A-Barcode 15-V1/2) (SEQ ID NO: 49)CCATCTCATCCCTGCGTGTCTCCGACTCAGTCTAGAGGTCGATAGAGTTTGATCCTGGCTCAG ForwardPrimer (Primer A-Barcode 16-V1/2) (SEQ ID NO: 50)CCATCTCATCCCTGCGTGTCTCCGACTCAGTCTGGATGACGATAGAGTTTGATCCTGGCTCAG ReversePrimer (Primer P1-V1/2) (SEQ ID NO: 33)CCTCTCTATGGGCAGTCGGTGATCTGCTGCCTYCCGTA

TABLE 5 Examples of V5/4 Primers. Barcodes are underlined, and the 16SVariable Region Homology is in bold. Forward Primer (Primer A-Barcode1-V5/4) (SEQ ID NO: 51)CCATCTCATCCCTGCGTGTCTCCGACTCAGCTAAGGTAACGATCCGTCAATTYYTTTRAGTTT ForwardPrimer (Primer A-Barcode 2-V5/4) (SEQ ID NO: 52)CCATCTCATCCCTGCGTGTCTCCGACTCAGTAAGGAGAACGATCCGTCAATTYYTTTRAGTTT ForwardPrimer (Primer A-Barcode 3-V5/4) (SEQ ID NO: 53)CCATCTCATCCCTGCGTGTCTCCGACTCAGAAGAGGATTCGATCCGTCAATTYYTTTRAGTTT ForwardPrimer (Primer A-Barcode 4-V5/4) (SEQ ID NO: 54)CCATCTCATCCCTGCGTGTCTCCGACTCAGTACCAAGATCGATCCGTCAATTYYTTTRAGTTT ForwardPrimer (Primer A-Barcode 5-V5/4) (SEQ ID NO: 55)CCATCTCATCCCTGCGTGTCTCCGACTCAGCAGAAGGAACGATCCGTCAATTYYTTTRAGTTT ForwardPrimer (Primer A-Barcode 6-V5/4) (SEQ ID NO: 56)CCATCTCATCCCTGCGTGTCTCCGACTCAGCTGCAAGTTCGATCCGTCAATTYYTTTRAGTTT ForwardPrimer (Primer A-Barcode 7-V5/4) (SEQ ID NO: 57)CCATCTCATCCCTGCGTGTCTCCGACTCAGTTCGTGATTCGATCCGTCAATTYYTTTRAGTTT ForwardPrimer (Primer A-Barcode 8-V5/4) (SEQ ID NO: 58)CCATCTCATCCCTGCGTGTCTCCGACTCAGTTCCGATAACGATCCGTCAATTYYTTTRAGTTT ForwardPrimer (Primer A-Barcode 9-V5/4) (SEQ ID NO: 59)CCATCTCATCCCTGCGTGTCTCCGACTCAGTGAGCGGAACGATCCGTCAATTYYTTTRAGTTT ForwardPrimer (Primer A-Barcode 10-V5/4) (SEQ ID NO: 60)CCATCTCATCCCTGCGTGTCTCCGACTCAGCTGACCGAACGATCCGTCAATTYYTTTRAGTTT ForwardPrimer (Primer A-Barcode 11-V5/4) (SEQ ID NO: 61)CCATCTCATCCCTGCGTGTCTCCGACTCAGTCCTCGAATCGATCCGTCAATTYYTTTRAGTTT ForwardPrimer (Primer A-Barcode 12-V5/4) (SEQ ID NO: 62)CCATCTCATCCCTGCGTGTCTCCGACTCAGTAGGTGGTTCGATCCGTCAATTYYTTTRAGTTT ForwardPrimer (Primer A-Barcode 13-V5/4) (SEQ ID NO: 63)CCATCTCATCCCTGCGTGTCTCCGACTCAGTCTAACGGACGATCCGTCAATTYYTTTRAGTTT ForwardPrimer (Primer A-Barcode 14-V5/4) (SEQ ID NO: 64)CCATCTCATCCCTGCGTGTCTCCGACTCAGTTGGAGTGTCGATCCGTCAATTYYTTTRAGTTT ForwardPrimer (Primer A-Barcode 15-V5/4) (SEQ ID NO: 65)CCATCTCATCCCTGCGTGTCTCCGACTCAGTCTAGAGGTCGATCCGTCAATTYYTTTRAGTTT ForwardPrimer (Primer A-Barcode 16-V5/4) (SEQ ID NO: 66)CCATCTCATCCCTGCGTGTCTCCGACTCAGTCTGGATGACGATCCGTCAATTYYTTTRAGTTT ReversePrimer (Primer P1-V5/4) (SEQ ID NO: 34)CCTCTCTATGGGCAGTCGGTGATAYTGGGYDTAAAGNG

The PCR is then run with the Thermocycler set to the followingconditions:

Step# Temp. Time Notes 1) 96° C. 1 minute 2) 96° C. 20 seconds 3) 42° C.30 seconds 4) 72° C. 30 seconds 5) — — Repeat 2-4 40x 6)  4° C.Indefinitely

Example 5 Purification of DNA from PCR Reactions

After barcoding and amplification of the extracted DNA, the resultingDNA reactions are purified to remove extraneous DNA sequences that arenot the targets for sequencing with standard gel electrophoresis and gelextraction. Gel extraction is performed using the QiaPrep Gel ExtractionMini kit (QIAGEN, Germantown, Md.).

Example 6 IonSphere Particle Labeling

All purified DNA samples from the PCR reactions are pooled together inequimolar ratios determined by NanoDrop (Thermo Scientific, Wilmington,Del.) and the known DNA fragment sizes. The pooled library is diluted toprecisely 0.08 μM and used as the DNA template for the OneTouchIonSphere Particle Labeling protocol as listed in the Ion OneTouch 200Template Kit v2 DL (Pub# MAN0007112, Revision: 5.0) in conjunction withthe Ion OneTouch 200 Template Kit v2 DL kit.

The OneTouch IonSphere Particle (ISP) Labeling protocol is followed witha few modifications to the “Add Ion OneTouch Reaction Oil” loading stepand the “Recover the Template-Positive ISPs” step. The changes are asfollows:

Add Ion OneTouch Reaction Oil

Add Ion OneTouch™ Reaction Oil through the sample port:

-   -   a. Set a P1000 pipette to 750 μL, and attach a new 1000-μL tip        to the pipette.    -   b. Fill the tip with 750 μL of Reaction Oil.    -   c. Insert the tip firmly into the sample port so that the tip is        perpendicular to the Ion OneTouch™ Plus Reaction Filter Assembly        and fully inserted into the sample port to form a tight seal.    -   d. Gently pipet 750 μL of the Reaction Oil through the sample        port. Keep the plunger of the pipette depressed to avoid        aspirating solution from the Ion PGM™ OneTouch Plus Reaction        Filter Assembly.    -   e. With the plunger still depressed, remove the tip from the        sample port, then appropriately discard the tip.    -   f. Set the P1000 pipette to 750 μL, and attach a new 1000-μL tip        to the pipette.    -   g. Fill the tip with 750 μL of Reaction Oil.    -   h. Insert the tip firmly into the sample port so that the tip is        perpendicular to the Ion OneTouch™ Plus Reaction Filter Assembly        and fully inserted into the sample port to form a tight seal.    -   i. Gently pipet 750 μL of the Reaction Oil through the sample        port, then keep the plunger of the pipette depressed.    -   j. With the plunger still depressed, remove the tip from the        sample port, then appropriately discard the tip.    -   k. If desired, gently dab a Kimwipes® disposable wiper around        the ports to remove any liquid.

Recover the Template-Positive ISPs

-   -   1. At the end of the run, ensure that you centrifuged the        samples. (Ensure that you have touched Next on the Centrifuge        screen to centrifuge the samples and that the home screen        displays after the centrifugation.)    -   2. Immediately after the centrifuge stops, remove and discard        the Recovery Router.    -   3. Carefully remove both Recovery Tubes from the instrument, and        put the two Recovery Tubes in a tube rack. You may see some        cloudiness in the tube, which is normal.    -   4. Label a new 1.5-mL LoBind Tube for the template-positive        ISPs.    -   5. Use a pipette to remove all but ˜100 μL of Ion OneTouch™        Recovery Solution from each Ion OneTouch™ Recovery Tube. Do not        disturb the pellet of template-positive ISPs.    -   6. Add 1 mL of Ion OneTouch Wash solution to one Recovery Tube        with the ISP pellet and resuspend the pellet by gently pipetting        up and down.    -   7. Transfer the Ion OneTouch Wash solution and resuspended ISPs        to the other Recovery Tube and resuspend the pellet by gently        pipetting up and down.    -   8. Transfer the ˜1.2 mL suspension to the new labeled tube.

Stopping Point: The template-positive ISPs with Ion OneTouch™ WashSolution may be stored at 2° C. to 8° C. for up to 3 days. Afterstorage, proceed to step 10.

-   -   Do not store the recovered ISPs in Ion OneTouch™ Recovery        Solution.    -   9. Centrifuge the template-positive ISP suspension for 2.5        minutes at 15,500×g.    -   10. Remove all but 100 μL of supernatant.    -   11. Vortex the pellet for 30 seconds to completely resuspend the        template-positive ISPs.    -   12. (Optional) Assess the quality of the unenriched,        template-positive ISPs.    -   13. Enrich the template-positive ISPs.

Example 7 IonSphere Particle Enrichment and DNA Sequencing IonSphereParticle Enrichment

The IonSphere Particle Enrichment protocol is performed as listed in theIon OneTouch 200 Template Kit v2 DL (Pub# MAN0007112, Revision: 5.0) inconjunction with the Ion OneTouch 200 Template Kit v2 DL kit (LifeTechnologies, Carlsbad, Calif.).

DNA Sequencing

The DNA Sequencing protocol is performed as listed in the Ion PGMSequencing Kit manuals for the appropriate sequencing length kit inconjunction with the Ion PGM Sequencing Kits. The only variation to theprotocol is a modification of the total flow cycle numbers whereby thetotal flow cycle number is increased by 80 flows above the kitspecifications.

Example 8 Computer-Based Genomic Analysis

Once sequencing is complete, individually barcoded sequence sets may bedownloaded from the Ion Torrent Browser interface. These are imported asFASTQ files into CLC Workbench. Each sequence set is then preferablyprocessed according to the following steps:

1. Sequences of a specific barcode are length selected and only 100 bplength sequences or greater are retained.

2. These sequences are BLASTed against a local 16S database of known,named, and non-redundant Eubacteria.

3. The resulting BLAST results are size sorted.

4. A size cut-off is selected for each BLAST results based on threefactors.

-   -   a. Distribution of the reads obtained for that given barcode and        the first “cluster” of sequence read lengths is selected with        the cut-off as high as possible to include this sequence        cluster.    -   b. If no cluster of sequences is apparent then approximately 100        of the longest sequences are selected for reporting.    -   c. Sequences less than 100 bp are not used for reporting.

5. The following statistical information is reported based on theprovided cut-off values:

-   -   a. >100 bp—The species for an individual sequence read is        correctly identified greater than 10% of the time.    -   b. >150 bp—The species for an individual sequence read is        correctly identified greater than 15% of the time.    -   c. >175 bp—The species for an individual sequence read is        correctly identified greater than 25% of the time.    -   d. >250 bp—The species for an individual sequence read is        correctly identified greater than 30% of the time.    -   e. >300 bp—The species for an individual sequence read is        correctly identified greater than 35% of the time.    -   f. >355 bp—The species for an individual sequence read is        correctly identified greater than 95% of the time.

6. Repeat positive results increased the chances of a correctly calledsample. Therefore, sequences are only reported if they comprise >1% ofthe total identified sequence reads and are represented by >5 sequencesin total. In this case a sample comprising 1% of a total sequence readwith a cut-off at 100 bp would have much less than a 1% chance (All 5wrong out of 100,000 chances=0.005%) of incorrectly identifying thespecies as an aggregate. Often times there are hundreds or thousands ofsequences that identify the same species, thus it is a statisticalcertainty that the species are correctly identified on the highest endsof the reporting ranges.

7. A report is generated that graphically displays the proportion of thetop 6 or less species identified. A table is also provided that liststhe sequence counts and relative percentages of all significantsequences (>1% contribution and 5 or more sequences). Treatmentresistance information is provided for each identified genus includingscientific and medical references containing that information.

Example 9 Pan-Bacterial Metagenomics Analysis No. 1

A dental sample from a patient was processed to extract the nucleicacids, prepare an ion amplicon library, purify the ion amplicon library,sequence the 16S rRNA in the library, and identify the species ofmicroorganisms present in the biological sample with a computer-basedgenomic analysis using the procedures described in Examples 1-8. PCRprimers were selected from those listed in Tables 4 and 5.

Sequence Information: 365,254 sequence reads were obtained for the givensample. The longest 252 sequences were analyzed and compared to allavailable prokaryotic species.

Results Confidence Profile (355): At the provided quality controlcut-off it is estimated that >95% of the sequence reads correctly listthe genus, while >95% of the sequence reads correctly list the species.

The identified species are shown in Table 6 and FIG. 4.

TABLE 6 Species identified by computer-based genomics analysis Number ofSpecies Sequences % Prevotella oralis 46 18%  Prevotella nigrescens 4016%  Prevotella oris 23 9% Selenomonas infelix 23 9% Porphyromonasendodontalis 17 7% Prevotella multiformis 13 5% Fusobacterium nucleatum12 5% Selenomonas sputigena 12 5% Prevotella intermedia 10 4% Prevotelladentalis 8 3% Prevotella oulorum 6 2%

The antibiotic susceptibility was determined and reported based on thegenera identified with the computer-based genomic analysis. The resultsare shown in Table 7.

TABLE 7 Antibiotic susceptibilities Description Genus Antibiotics NotedResistance Prevotella oralis Metronidazole, Metronidazole, amoxicillin,amoxycillin/clavulanate, amoxycillin/clavulanate, doxycycline,ureidopenicilins, ureidopenicilins, carbapenems, carbapenems,cephalosporins, cephalosporins, clindamycin, clindamycin, andclarithromycin, chloramphenicol, chloramphenicol. moxifloxacin, andlevofloxacin. Prevotella nigrescens Refer to Prevotella oralis. Refer toPrevotella oralis. Prevotella oris Refer to Prevotella oralis. Refer toPrevotella oralis. Selenomonas infelix Azithromycin. Erythromycin.Porphyromonas Penicillins (ampicillin, Unknown endodontalis amoxicillin,ticarcillin), cephaloridine, cephalothin, cefamandole, cefotaxime,cefoxitin, cefuroxime, imipenem, piperacillin, erythromycin,oleandomycin, spiramycin, clindamycin, tetracycline, metronidazole,azithromycin, and doxycycline. Prevotella multiformis Refer toPrevotella oralis. Refer to Prevotella oralis.

Prevotella Species:

Antibiotics: Antibiotic susceptibility varies among Prevotella species.Antibiotics used to treat Prevotella infections include: metronidazole,amoxycillin/clavulanate, doxycycline, ureidopenicilins, carbapenems,cephalosporins, clindamycin, and chloramphenicol.Resistance: Resistance to metronidazole, amoxicillin,amoxycillin/clavulanate, ureidopenicilins, carbapenems, cephalosporins,clindamycin, clarithromycin, chloramphenicol, moxifloxacin, andlevofloxacin have been reported.

References:

-   Flynn, M. J., Li, G., Slots, J. (1994). Mitsuokella dentalis in    human periodontitis. Oral Microbiol. Immunol. 9, 248-250.-   Mosca A, Miragliotta L, Iodice M A, et al. Antimicrobial profiles of    Prevotella spp. and Fusobacterium nucleatum isolated form    periodontal infections in a selected area of southern Italy. Int J    of Antimicro Agents December 2007; 30(6):521-4.-   Shah, H. N., Collins, D. M. (1990). Prevotella, a new genus to    include Bacteroides melaminogenicus and related species formerly    classified in the genus Bacterioides. Int. J. syst. Bacteriol. 40,    205-208.

Selenomonas Species:

Antibiotics: Active antibiotics include: Azithromycin.Resistance: Inactive antibiotics: Erythromycin.

References:

-   Comparative in-vitro activity of azithromycin, macrolides    (erythromycin, clarithromycin and spiramycin) and streptogramin RP    59500 against oral organisms. Williams, J. D., Maskell, J. P.,    Shain, H., Chrysos, G., Sefton, A. M., Fraser, H. Y.,    Hardie, J. M. J. Antimicrob. Chemother. (1992).

Porphyromonas Species:

Antibiotics: Antibiotic susceptibility varies among Porphyromonasspecies. Antibiotics used to treat Peptostreptococcus infectionsinclude: Penicillins (ampicillin, amoxicillin, ticarcillin),cephaloridine, cephalothin, cefamandole, cefotaxime, cefoxitin,cefuroxime, imipenem, piperacillin, erythromycin, oleandomycin,spiramycin, clindamycin, tetracycline, metronidazole, azithromycin, anddoxycycline.Resistance: Resistance to antibiotics has not been reported to asignificant degree.

References:

-   Andres M T, Chung W O, Roberts M C, and Fierro J F. Antimicrobial    susceptibilities of Porphyromonas gingivalis, Prevotella intermedia,    and Prevotella nigrescens spp. Isolated in Spain. Antimicrob Agents    Chemoth. November 1998; 42(11):3022-3.-   Japoni A, Vazin A, Noushadi S, Kiany F, et al. Antibacterial    susceptibility patterns of Porphyromonas gingivalis isolated from    chronic periodontitis patients. November 2011; 16(7):e1031-5.-   Kulik E M, Lenkeit K, Chenaux S, and Meyer J. Antimicrobial    susceptibility of periodontopathogenic bacteria. J Antimicrob    Chemother March 2008; 61(5): 1087-91.-   Pajukanta R, Asikainen S, Forsblom B, Saarela M, Jousimies-Somer H.    β-Lactamase production and in vitro antimicrobial susceptibility of    Porphyromonas gingivalis. FEMS Immunol Med. Microbiol. 1993;    6:241-244.

Fusobacterium Species:

Antibiotics: Antibiotic susceptibility varies among Fusobacteriumspecies. Treatment of Fusobacterium infections depends on the site ofinfections. Antibiotics used to treat Fusobacterium infections include:Metronidazole, piperacillin/tazobactum, ticarcillin/clavulanate,amoxicillin/sulbactum, ampicillin/sulbactum, ertupenem, imipenem,meropenem, clindamycin, and cefoxitin.Resistance: Some resistantance to penicillin noted with widespreadresistance to erythromycin and other macrolides.

References:

-   Citron, D. M., Poxton, I. R., & Baron, E. J. (2007). Bacteroides,    Porphyromonas, Prevotella, Fusobacterium, and Other Anaerobic    Gram-Negative Rods. In P. R. Murray, E. J. Baron, M. L.    Landry, J. H. Jorgensen & M. A. Pfaller (Eds.), Manual of Clinical    Microbiology (9th ed., pp. 911-932). Washington, D.C.: ASM Press.-   Riordan, T. (2007). Human infection with Fusobacterium necrophorum    (Necrobacillosis), with a focus on Lemierre's syndrome. Clinical    Microbiology Reviews, 20(4), 622-659. doi:10.1128/CMR.00011-07.-   Boyanova, L., Kolarov, R., & Mitov, I. (2007). Antimicrobial    resistance and the management of anaerobic infections. Expert Review    of Anti-Infective Therapy, 5(4), 685-701.

Example 10 Pan-Bacterial Metagenomics Analysis No. 2

A dental sample from a patient was processed to extract the nucleicacids, prepare an ion amplicon library, purify the ion amplicon library,sequence the 16S rRNA in the library, and identify the species ofmicroorganisms present in the biological sample with a computer-basedgenomic analysis using the procedures described in Examples 1-8. PCRprimers were selected from those listed in Tables 4 and 5.

Sequence Information: 177,821 sequence reads were obtained for the givensample. The longest 285 sequences were analyzed and compared to allavailable prokaryotic species.

Results Confidence Profile (355): At the provided quality controlcut-off it is estimated that >95% of the sequence reads correctly listthe genus, while >95% of the sequence reads correctly list the species.

The identified species are shown in Table 8 and FIG. 5.

TABLE 8 Species identified by computer-based genomics analysis Number ofSpecies Sequences % Capnocytophaga gingivalis 56 20%  Prevotella oris 5519%  Gemella sanguinis 53 19%  Neisseria bacilliformis 37 13% Leptotrichia shahii 22 8% Prevotella oulorum 10 4% Selenomonas infelix 83% Alysiella filiformis 5 2% Streptococcus intermedius 5 2%

The antibiotic susceptibility was determined and reported based on thegenera identified with the computer-based genomic analysis. The resultsare shown in Table 9.

TABLE 9 Antibiotic susceptibilities Description Genus Antibiotics NotedResistance Capnocytophaga Penicillin G, ampicillin, third Gentamycin andPenicillin G. gingivalis generation cephalosporins, tetracyclines,clindamycin, and chloromphenicol Prevotella oris Metronidazole,Metronidazole, amoxicillin, amoxycillin/clavulanate,amoxycillin/clavulanate, doxycycline, ureidopenicilins,ureidopenicilins, carbapenems, carbapenems, cephalosporins,cephalosporins, clindamycin, clindamycin, and clarithromycin,chloramphenicol, chloramphenicol. moxifloxacin, and levofloxacin Gemellasanguinis Penicillin, ampicillin, Sulfonamides and trimethoprim,cephalosporins, tetracyclines, and aminoglycosides. chloramphenicol,lincomycins and tetrasulfathiazole. Neisseria bacilliformis Cefotaximeand ceftriaxone Penicillin Leptotrichia shahii Unknown UnknownPrevotella oulorum Metronidazole, Metronidazole, amoxicillin,amoxycillin/clavulanate, amoxycillin/clavulanate, doxycycline,ureidopenicilins, ureidopenicilins, carbapenems, carbapenems,cephalosporins, cephalosporins, clindamycin, clindamycin, andchloramphenicol clarithromycin, chloramphenicol, moxifloxacin, andlevofloxacin.

Capnocytophaa Species:

Antibiotics: Capnocytophaga is susceptible to penicillin G, ampicillin,third generation cephalosporins, tetracyclines, clindamycin, andchloromphenicol.Resistance: Species has shown resistance to gentamycin and penicillin Gin some cases.

References:

-   Brenner D J, Hollis D G, Fanning G R, and Weaver R E. 1989.    Capnocytophaga canimorsus sp. nov. (Formerly CDC Group DF-2), a    Cause of Septicemia following Dog Bite, and C. cynodegmi sp. nov., a    Cause of Localized Wound Infection following Dog Bite. Journal of    Clinical Microbiology 27 (2): 231-235.-   Lion C, Escande F and Burdin J C. 1996. Capnocytophaga canimorsus    Infections in Human: Review of the Literature and Cases Report.    European Journal of Epidemiology 12 (5): 521-533.

Prevotella Species:

Antibiotics: Antibiotic susceptibility varies among Prevotella species.Antibiotics used to treat Prevotella infections include: metronidazole,amoxycillin/clavulanate, doxycycline, ureidopenicilins, carbapenems,cephalosporins, clindamycin, and chloramphenicol.Resistance: Resistance to metronidazole, amoxicillin,amoxycillin/clavulanate, ureidopenicilins, carbapenems, cephalosporins,clindamycin, clarithromycin, chloramphenicol, moxifloxacin, andlevofloxacin have been reported.

References:

-   Flynn, M. J., Li, G., Slots, J. (1994). Mitsuokella dentalis in    human periodontitis. Oral Microbiol. Immunol. 9, 248-250.-   Mosca A, Miragliotta L, Iodice M A, et al. Antimicrobial profiles of    Prevotella spp. and Fusobacterium nucleatum isolated form    periodontal infections in a selected area of southern Italy. Int J    of Antimicro Agents December 2007; 30(6):521-4.-   Shah, H. N., Collins, D. M. (1990). Prevotella, a new genus to    include Bacteroides melaminogenicus and related species formerly    classified in the genus Bacterioides. Int. J. syst. Bacteriol. 40,    205-208.

Gemella Species:

Antibiotics: Active antibiotics include: penicillin, ampicillin,cephalosporins, tetracyclines, chloramphenicol, lincomycins andtetrasulfathiazole.Resistance: Inactive antibiotics include: sulfonamides and trimethoprim,and aminoglycosides.

References:

-   Collins, M. D. (2006). The Genus Gemella. In M. Dworkin, S.    Falkow, E. Rosenberg, K. H. Schleifer & E. Stackebrandt (Eds.), The    Prokaryotes (3rd ed., pp. 511-518). New York: Springer.-   Collins, M. D. (2006). The Genus Gemella. In M. Dworkin, S.    Falkow, E. Rosenberg, K. H. Schleifer & E. Stackebrandt (Eds.), The    Prokaryotes (3rd ed., pp. 511-518). New York: Springer.-   Buu-Hoi, A., Sapoetra, A., Branger, C., & Acar, J. F. (1982).    Antimicrobial susceptibility of Gemella haemolysans isolated from    patients with subacute endocarditis. European Journal of Clinical    Microbiology, 1(2), 102-106.-   Hamrah, P., Ritterband, D., Seedor, J., & Eiferman, R. A. (2006).    Ocular infection secondary to gemella. Graefe's Archive for Clinical    and Experimental Ophthalmology=Albrecht Von Graefes Archiv Fur    Klinische Und Experimentelle Ophthalmologic, 244(7), 891-892.

Neisseria Species:

Antibiotics: Active antibiotics for Neisseria include third-generationcephalosporin antibiotics such as cefotaxime and ceftriaxone.Resistance: Some species have been shown to be resistant to thepenicillin family of antibiotics.

References:

-   Tunkel A R, Hartman B J, Kaplan S L, Kaufman B A, Roos K L, Scheld W    M, Whitley R J (November 2004). “Practice guidelines for the    management of bacterial meningitis”. Clin Infect Dis 39 (9):    1267-84. “UK doctors advised gonorrhoea has turned drug resistant    BBC News. 10 Oct. 2011.

Leptotrichia Species:

Antibiotics: Antibiotic susceptibility for Leptotrichia has not beenextensively studied.Resistance: Antibiotic resistance for Leptotrichia has not beenextensively studied.

References:

-   Eribe E R, Paster B J, Caugant D A, Dewhirst F E, Stromberg V K,    Lacy G H, Olsen I. Genetic diversity of Leptotrichia and description    of Leptotrichia goodfellowii sp. nov., Leptotrichia hofstadii sp.    nov., Leptotrichia shahii sp. nov. and Leptotrichia wadei sp.    November Institute of Oral Biology, Dental Faculty, University of    Oslo, POB 1052, Blindern, N-0316 Oslo, Norway.

Prevotella Species:

Antibiotics: Antibiotic susceptibility varies among Prevotella species.Antibiotics used to treat Prevotella infections include: metronidazole,amoxycillin/clavulanate, doxycycline, ureidopenicilins, carbapenems,cephalosporins, clindamycin, and chloramphenicol.Resistance: Resistance to metronidazole, amoxicillin,amoxycillin/clavulanate, ureidopenicilins, carbapenems, cephalosporins,clindamycin, clarithromycin, chloramphenicol, moxifloxacin, andlevofloxacin have been reported.

References:

-   Flynn, M. J., Li, G., Slots, J. (1994). Mitsuokella dentalis in    human periodontitis. Oral Microbiol. Immunol. 9, 248-250.-   Mosca A, Miragliotta L, Iodice M A, et al. Antimicrobial profiles of    Prevotella spp. and Fusobacterium nucleatum isolated form    periodontal infections in a selected area of southern Italy. Int J    of Antimicro Agents December 2007; 30(6):521-4.-   Shah, H.N., Collins, D. M. (1990). Prevotella, a new genus to    include Bacteroides melaminogenicus and related species formerly    classified in the genus Bacterioides. Int. J.

Selenomonas Species:

Antibiotics: Active antibiotics include: Azithromycin.Resistance: Inactive antibiotics: Erythromycin.

References:

-   Comparative in-vitro activity of azithromycin, macrolides    (erythromycin, clarithromycin and spiramycin) and streptogramin RP    59500 against oral organisms. Williams, J. D., Maskell, J. P.,    Shain, H., Chrysos, G., Sefton, A. M., Fraser, H. Y.,    Hardie, J. M. J. Antimicrob. Chemother. (1992).

Alysiella Species:

Antibiotics: Antibiotic susceptibility for Alysiella has not beenextensively studied.Resistance: Antibiotic resistance for Alysiella has not been extensivelystudied.

References:

-   Cheng-Hui Xie and Akira Yokota, Transfer of the misnamed [Alysiella]    sp. IAM 14971 (=ATCC 29468) to the genus Moraxella as Moraxella    oblonga sp. nov., International Journal of Systematic and    Evolutionary Microbiology, January 2005 Vol. 55 no. 1 331-334.

Streptococcus Species:

Antibiotics: Active antibiotics for Streptococcus include: penicillin,amoxicillin, intramuscular benzathine pencicillin G, erythromycin,clindamycin, cephalosporins, cephalexin, cefuroxime axetil, andcefdinir.Resistance: Penicillin has been reported to be ineffective in somecases. B-lactams and macrolides have been reported as an inactiveantibiotics.

References:

-   Hooton T M. A comparison of azithromycin and penicillin V for the    treatment of streptococcal pharyngitis. Am J. Med. 1991 Sep. 12;    91(3A):23S-26S.PubMed Cohen R, Reinert P, De La Rocque F, Levy C,    Boucherat M, Robert M, Navel M, Brahimi N, Deforche D, Palestro B,    Bingen E. Comparison of two dosages of azithromycin for three days    versus penicillin V for ten days in acute group A streptococcal    tonsillopharyngitis. Pediatr Infect Dis J. 2002 April;    21(4):297-303.-   Casey J R, Pichichero M E. Meta-analysis of cephalosporin versus    penicillin treatment of group A streptococcal tonsillopharyngitis in    children. Pediatrics. 2004 April; 113(4):866-82.-   Scholz H. Streptococcal-A tonsillopharyngitis: a 5-day course of    cefuroxime axetil versus a 10-day course of penicillin V. results    depending on the children's age. Chemotherapy. Baltimore RS    (February 2010). “Re-evaluation of antibiotic treatment of    streptococcal pharyngitis”. Curr. Opin. Pediatr. 22 (1): 77-82.-   Shulman, S T; Bisno, A L; Clegg, H W; Gerber, M A; Kaplan, E L; Lee,    G; Martin, J M; Van Beneden, C (2012 Sep. 9). “Clinical Practice    Guideline for the Diagnosis and Management of Group A Streptococcal    Pharyngitis: 2012 Update by the Infectious Diseases Society of    America.”. Clinical infectious diseases: an official publication of    the Infectious Diseases Society of America.-   Choby B A (March 2009). “Diagnosis and treatment of streptococcal    pharyngitis”. Am Fam Physician 79 (5): 383-90.-   Albrich, W; Monnet, D L; Harbarth, S (2004). “Antibiotic selection    pressure and resistance in Streptococcus pneumoniae and    Streptococcus pyogenes”. Emerging Infect. Dis. 10 (3): 514-7.    PMC 3322805. PMID 15109426.

Example 11 Pan-Bacterial Metagenomics Analysis No. 3

A dental sample from a patient was processed to extract the nucleicacids, prepare an ion amplicon library, purify the ion amplicon library,sequence the 16S rRNA in the library, and identify the species ofmicroorganisms present in the biological sample with a computer-basedgenomic analysis using the procedures described in Examples 1-8. PCRprimers were selected from those listed in Tables 4 and 5.

Sequence Information: 330,413 sequence reads were obtained for the givensample. The longest 268 sequences were analyzed and compared to allavailable prokaryotic species.

Results Confidence Profile (355): At the provided quality controlcut-off it is estimated that >95% of the sequence reads correctly listthe genus, while >95% of the sequence reads correctly list the species.

The identified species are shown in Table 10 and in FIG. 6.

TABLE 10 Species identified by computer-based genomics analysis Numberof Species Sequences % Actinomyces naeslundii 198 74%  Neisserialactamica 10 4% Streptococcus gordonii 10 4% Streptococcus mutans 9 3%Granulicatella adiacens 6 2% Streptococcus infantis 6 2% Streptococcusoralis 6 2%

The antibiotic susceptibility was determined and reported based on thegenera identified with the computer-based genomic analysis. The resultsare shown below and in Table 11.

TABLE 11 Antibiotic susceptibilities Description Genus Antibiotics NotedResistance Actinomyces Penicillin, amoxicillin, Metronidazole, TMP-SMX,naeslundii doxycycline, erythromycin, and ceftazidime, aminoglycosides,clindamycin. Other agents having oxacillin, and fluoroquinolones.limited date include: clarithromycin, azithromycin, imipenem,cefotaxime, and ceftiaxone. Neisseria Cefotaxime and ceftriaxone.Penicillin lactamica Streptococcus Penicillin, amoxicillin, Penicillin,B-lactams, and gordonii intramuscular benzathine macrolides. pencicillinG, erythromycin, clindamycin, cephalosporins, cephalexin, cefuroximeaxetil, and cefdinir. Streptococcus Refer to Streptococcus mutans Referto Streptococcus mutans mutans Granulicatella Penicillin andceftriaxone, Penicillin, cefotaxime, and adiacens vancomycin.ampicillin, azithromycin. Resistance to beta- ampicillin-sulbactam,lactam and macrolide antibiotics amoxicillin-clavulanate, has beendescribed. cefazolin, cefinetazole, or meropenem. Streptococcus Refer toStreptococcus mutans Refer to Streptococcus mutans infantis

Actinomyces Species:

Antibiotics: Active antibiotics for treatment of Actinomyces includepenicillin, amoxicillin, doxycycline, erythromycin, and clindamycin.Other agents having limited date include: clarithromycin, azithromycin,imipenem, cefotaxime, and ceftiaxone.Resistance: Antibiotic resistance for Actinomyces include metronidazole,TMP-SMX, ceftazidime, aminoglycosides, oxacillin, and fluoroquinolones.

References:

-   Smith A J et al: Antimicrobial susceptibility testing of Actinomyces    species with 12 antimicrobial agents. J Antimicrob Chemother 56:407,    2005.

Neisseria Species:

Antibiotics: Active antibiotics for Neisseria include third-generationcephalosporin antibiotics such as cefotaxime and ceftriaxone.Resistance: Some species have been shown to be resistant to thepenicillin family of antibiotics.

References:

-   Tunkel A R, Hartman B J, Kaplan S L, Kaufman B A, Roos K L, Scheld W    M, Whitley R J (November 2004). “Practice guidelines for the    management of bacterial meningitis”. Clin Infect Dis 39 (9):    1267-84. “UK doctors advised gonorrhoea has turned drug resistant    BBC News. 10 Oct. 2011.

Streptococcus Species:

Antibiotics: Active antibiotics for Streptococcus include: penicillin,amoxicillin, intramuscular benzathine pencicillin G, erythromycin,clindamycin, cephalosporins, cephalexin, cefuroxime axetil, andcefdinir.Resistance: Penicillin has been reported to be ineffective in somecases. B-lactams and macrolides have been reported as an inactiveantibiotics.

References:

-   Hooton T M. A comparison of azithromycin and penicillin V for the    treatment of streptococcal pharyngitis. Am J. Med. 1991 Sep. 12;    91(3A):23S-26S.PubMed-   Cohen R, Reinert P, De La Rocque F, Levy C, Boucherat M, Robert M,    Navel M, Brahimi N, Deforche D, Palestro B, Bingen E. Comparison of    two dosages of azithromycin for three days versus penicillin V for    ten days in acute group A streptococcal tonsillopharyngitis. Pediatr    Infect Dis J. 2002 April; 21(4):297-303.-   Casey J R, Pichichero M E. Meta-analysis of cephalosporin versus    penicillin treatment of group A streptococcal tonsillopharyngitis in    children. Pediatrics. 2004 April; 113(4):866-82.-   Scholz H. Streptococcal-A tonsillopharyngitis: a 5-day course of    cefuroxime axetil versus a 10-day course of penicillin V. results    depending on the children's age. Chemotherapy.-   Baltimore R S (February 2010). “Re-evaluation of antibiotic    treatment of streptococcal pharyngitis”. Curr. Opin. Pediatr. 22    (1): 77-82.-   Shulman, S T; Bisno, A L; Clegg, H W; Gerber, M A; Kaplan, E L; Lee,    G; Martin, J M; Van Beneden, C (2012 Sep. 9). “Clinical Practice    Guideline for the Diagnosis and Management of Group A Streptococcal    Pharyngitis: 2012 Update by the Infectious Diseases Society of    America.”. Clinical infectious diseases: an official publication of    the Infectious Diseases Society of America.-   Choby B A (March 2009). “Diagnosis and treatment of streptococcal    pharyngitis”. Am Fam Physician 79 (5): 383-90.-   Albrich, W; Monnet, D L; Harbarth, S (2004). “Antibiotic selection    pressure and resistance in Streptococcus pneumoniae and    Streptococcus pyogenes”. Emerging Infect. Dis. 10 (3): 514-7.    PMC 3322805. PMID 15109426.

Granulicatella Species:

Antibiotics: Active antibiotics against Granulicatella species include:penicillin and ceftriaxone, vancomycin. ampicillin,ampicillin-sulbactam, amoxicillin-clavulanate, cefazolin, cefmetazole,or meropenem.Resistance: Inactive antibiotics: penicillin, cefotaxime, andazithromycin. Resistance to beta-lactam and macrolide antibiotics hasbeen described.

References:

-   Sheng Kai Tung and Tsung Chain Chang, Molecular Detection of Human    Bacterial Pathogens, Edited by Dongyou Liu CRC Press 2011, Pages    249-255.    Levin, Yana D. MD; Petronaci, Carol-Lynn M D. Isolation of    Abiotrophia/Granulicatella Species from a Brain Abscess in an Adult    Patient Without Prior History of Neurosurgical Instrumentation    Southern Medical Journal: April 2010-Volume 103-Issue 4-pp 386-387.-   Chung-Hsin Liao, Lee-Jene Teng, Po-Ren Hsuch, Yu-Chi Chen, Li-Min    Huang, Shan-Chwen Chang, and Shen-Wu Ho. Nutritionally Variant    Streptococcal Infections at a University Hospital in Taiwan: Disease    Emergence and High Prevalence of β-Lactam and Macrolide Resistance.    Oxford Journals, Medicine Clinical Infectious Diseases, Volume 38,    Issue 3Pp. 452-455.-   Jason C. Gardenier, Tjasa Hranjec, Robert G. Sawyer, and Hugo    Bonatti, Granulicatella adiacens Bacteremia in an Elderly Trauma    Patient. Surgical Infections Volume 12, Number 3, 2011.

Example 12 Analysis of 16S rRNA Variable Regions

The oligonucleotides tested were fusion oligonucleotides as describedherein. The oligonucleotides had primer sequences that anneal to theindicated regions on the 16S gene, but they also contain the adaptersequences to make them compatible with sequencing.

An objective of this analysis was to identify important factors foridentification of bacteria via 16S sequencing. An equal distributionacross four 16S rRNA variable regions (V1/2, V3/2, V3/4, and V5/4) wasused to derive this data. The designation “V1/2” indicates that theoligonucleotide allows for sequencing of V1 in the direction of V2, thedesignation “V3/2” indicates that the oligonucleotide allows forsequencing of V3 in the direction of V2, etc. The fraction of the timethat Ralstonia solanacearum was correctly identified was plotted basedon the length of the obtained reads.

As can be seen in FIG. 7A, the longer reads resulted in more accurateidentification of the bacterial species. This analysis was repeated withseveral other species and similar results were obtained (data notshown). At read lengths of about 250 bp, the accuracy of speciesidentification approached 100% correct identification. Thus, the lengthof the reads is one of the most important factors to correctly identifya bacterial species. Future selection processes were directly focused onobtaining the longest reads and analyzing the longest reads available.

Also, as expected the number of sequences obtained at longer sizes dropas well. FIG. 7B presents a compilation of cutoffs and the percentage ofthe sequences in that category from seven different runs.

Having identified the length of the reads as an important factor foraccurate identification of bacterial species based on 16S rRNAsequencing, the next objective of the analysis was to determine which16S variable region resulted in the longest read lengths. As can be seenin Table 12, consistently regions V1/2 and V5/4 produced the longestreads even when the total number of sequences across two differentbarcodes varied by over double the amount (85574 and 269817,respectively). Ultimately, the extra basepairs translate into longerreads and more accurate identifications.

TABLE 12 Average Read Length Obtained with Oligonucleotides TargetingSpecific 16S rRNA Variable Regions Total Number Bar Code V1/2 V3/2 V3/4V5/4 of Sequences BC005 155.23 144.86 137.70 162.94 85574 BC006 157.70136.69 145.72 151.81 269817

These regions were also tested to see if the resulting number ofsequences skewed in any particular manner. It was found that for manybacterial species regions V1/2 and V5/4 naturally produced more useablesequences. Table 13 presents an example of one of these analyses.

TABLE 13 Summary of the number of sequences 150 bp or longer obtainedfrom a sample of Bordatella persussis with the OligonucleotidesTargeting Specific 16S rRNA Variable Regions Library Bar Code V1/2 V3/2V3/4 V5/4 Unknown Sum L6 BC003 32566 1631 74 66858 1808 102937 L6 BC00446781 23247 337 45510 1791 117666 Library Bar Code V1/2 V3/2 V3/4 V5/4Unknown L6 BC003 31.6% 1.6% 0.1% 65.0% 1.8% L6 BC004 39.8% 19.8% 0.3%38.7% 1.5%

rRNA variable regions V1/2 and V5/4 were selected for further analysis.Quite a few identification runs were performed using these regions toconfirm that they consistently provided longer reads and more accurategenus and species identifications. From this additional experimentation,it was determined that the use of both regions (i.e., V1/2 and V5/4) ispreferable because the various bacteria were identified more accuratelyto the Genus and Species level when both variable regions were sequencedand analyzed (see Table 14). This effect can be seen amongst not onlythe species tested but with the barcodes selected as well. Using theseparameters for bacterial identifications in the samples, generally thegenus was accurately identified greater than 95% of the time and thespecies was accurately identified greater than 30% of the time.

TABLE 14 Identification of bacterial genus and species in controlsamples using oligonucleotides targeting the V1/2 and V5/4 variableregions of the 16S rRNA. The percentages shown indicate the level ofaccuracy achieved in correctly identifying the bacterial genus andspecies in the sample. Genus Level Species Level Region Region RegionRegion Barcode Control ID % ID 1/2 5/4 % ID 1/2 5/4 011 Mycoplasma98.94% 94.89% 5.11% 98.94% 94.89% 5.11% pneumoniae 010 Ralstonia 99.38%75.70% 24.30% 75.22% 100.00% 0.00% solanacearum 005 Ralstonia 99.60%69.17% 30.83% 68.82% 100.00% 0.00% solanacearum 005 Ralstonia 99.62%77.45% 22.55% 77.15% 100.00% 0.00% solanacearum 007 Acholeplasma 99.74%71.41% 28.59% 97.86% 72.78% 27.22% laidlawii 012 Ralstonia 99.36% 72.02%27.98% 71.55% 100.00% 0.00% solanacearum 006 Mycoplasma 99.84% 0.43%99.57% 99.84% 0.43% 99.57% arthritidis 007 Mycoplasma 99.86% 97.05%2.95% 99.86% 97.05% 2.95% fermentans 012 Ralstonia 99.50% 45.38% 54.62%45.13% 99.97% 0.03% solanacearum 012 Ralstonia 99.64% 76.18% 23.82%75.91% 99.98% 0.02% solanacearum 012 Ralstonia 98.90% 42.44% 57.56%41.93% 100.00% 0.00% solanacearum 012 Ralstonia 99.65% 68.87% 31.13%68.62% 100.00% 0.00% solanacearum 012 Ralstonia 99.65% 68.89% 31.11%68.62% 99.99% 0.01% solanacearum

It was also discovered that the number of reads representing any givenorganism from region V1/2 and V5/4 start to even out given increasinglylong read lengths as seen in FIG. 8. Also as the number of >100 bpsequences over various cutoffs were examined it became apparent thatthere is a consistent result obtained when looking at the two selectedregions (see FIGS. 9A, 9B, 10A, and 10B).

Thus, the analysis revealed the surprising result that sequencing the16S variable regions of V1, V2, V4, and V5 produced the most accuratebacterial identifications. In particular, sequencing from V1 into V2 andfrom V5 into V4 proved to generate the longest reads and the mostaccurate identifications of bacterial genera and species.

Example 13 Further Analysis of 16S rRNA Variable Regions

Additional analysis was performed to confirm that 16S rRNA hypervariableregions 1/2 and 5/4 produce superior results over other hypervariableregions. This analysis revealed that regions 1/2 and 5/4 gave totalaverage lengths (before any size filtering) of 156.3 and 171.4respectively, while regions 3/2 and 3/4 resulted in 120.5 and 140.8,respectively (see Table 15). This length difference was also accompaniedby a staggering difference in sequence read number with regions 1/2 and5/4 resulting in a respective 106151.5 and 90913.7 sequences (onaverage), while 3/2 and 3/4 resulted in a meager 4942.7 and 433.0average sequences, respectively (see Table 16).

TABLE 15 Average lengths of sequencing reads using oligonucleotidestargeting 16S rRNA variable regions V1/2, V3/2, V3/4, and V5/4.Run/Barcodes Regions L6BC003 L6BC004 L7BC003 L7BC004 L9BC007 L9BC008Average 1/2 134.2 166.7 163.7 165.5 154.6 153.0 156.3 3/2 133.1 108.6119.5 118.3 118.4 125.4 120.5 3/4 130.7 132.6 141.7 140.9 148.9 149.9140.8 5/4 171.3 168.3 172.8 177.6 169.2 169.0 171.4

TABLE 16 Average sequence read numbers using oligonucleotides targeting16S rRNA variable regions V1/2, V3/2, V3/4, and V5/4. Run/BarcodesRegions L6BC003 L6BC004 L7BC003 L7BC004 L9BC007 L9BC008 Average 1/232957 47370 159605 163316 131133 102528 106151.5 3/2 1641 23420 21591486 651 299 4942.7 3/4 81 356 569 533 545 514 433.0 5/4 68107 4632596003 210504 81332 43211 90913.7

All of this taken together resulted in higher identification rates fromregions 1/2 and 5/4 over 3/2 and 3/4. This is shown in looking at thecorrect identification rates to the genus level with 1/2 identifying52.2% of the sequences correctly, 5/4 identifying 44.3%, 3/2 onlyidentifying 2.4%, and 3/4 identifying 0.2% (see Tables 17 and 18). Thisresult was not expected based on previous results and could be due toinherent bias or aspects of the sequencing set up.

It was found that using both of V1/2 and V5/4 oligonucleotides forsequencing was preferable because they had slightly differenteffectiveness identifying various bacterial genera and species.Increasing the detection depth was useful by including both and allowedverification of some of the sequenced organisms by having independentsequence confirmation from two regions (see Table 19).

TABLE 17 Percentage of sequence counts that correctly identified thegenus of control samples containing known bacterial microorganisms usingoligonucleotides targeting 16S rRNA variable regions V1/2, V3/2, V3/4,and V5/4. Identification Regions Correct Incorrect Region Total 1/252.2% 0.2% 52.4% 3/2 2.4% 0.1% 2.4% 3/4 0.2% 0.0% 0.2% 5/4 44.3% 0.6%44.9%

TABLE 18 Total sequence read numbers resulting in correct identificationof the bacterial genus of control samples using oligonucleotidestargeting 16S rRNA variable regions V1/2, V3/2, V3/4, and V5/4.Identification Regions Correct Incorrect Region Total 1/2 634646 2263636909 3/2 28836 820 29656 3/4 2335 263 2598 5/4 537587 7895 545482Total 1214645

TABLE 19 Percentages of correctly identified bacterial genera usingoligonucleotides targeting 16S rRNA variable regions V1/2, V3/2, V3/4,and V5/4 Region 1/2 Reads % Identified Borrelia 13876 42.1% Bordatella18707 56.8% Off Target 374 1.1% Total 32957 100.0% Region 1/2 Reads %Identified Mycoplasma 67152 42.1% Bordatella 92142 57.7% Off Target 3110.2% Total 159605 100.0% Region 1/2 Reads % Identified Borrelia 4113331.4% Bordatella 89428 68.2% Off Target 572 0.4% Total 131133 100.0%Region 3/2 Reads % Identified Borrelia 543 33.1% Bordatella 970 59.1%Off Target 128 7.8% Total 1641 100.0% Region 3/2 Reads % IdentifiedMycoplasma 345 16.0% Bordatella 1682 77.9% Off Target 132 6.1% Total2159 100.0% Region 3/2 Reads % Identified Borrelia 146 22.4% Bordatella381 58.5% Off Target 124 19.0% Total 651 100.0% Region 3/4 Reads %Identified Borrelia 30 37.0% Bordatella 37 45.7% Off Target 14 17.3%Total 81 100.0% Region 3/4 Reads % Identified Mycoplasma 62 10.9%Bordatella 470 82.6% Off Target 37 6.5% Total 569 100.0% Region 3/4Reads % Identified Borrelia 104 19.1% Bordatella 382 70.1% Off Target 5910.8% Total 545 100.0% Region 5/4 Reads % Identified Borrelia 4459965.5% Bordatella 22984 33.7% Off Target 524 0.8% Total 68107 100.0%Region 5/4 Reads % Identified Mycoplasma 18177 18.9% Bordatella 7616079.3% Off Target 1666 1.7% Total 96003 100.0% Region 5/4 Reads %Identified Borrelia 36411 44.8% Bordatella 43794 53.8% Off Target 11271.4% Total 81332 100.0% Region 1/2 Reads % Identified Bartonella 3097465.4% Borrelia 7689 16.2% Bordatella 8414 17.8% Off Target 293 0.6%Total 47370 100.0% Region 1/2 Reads % Identified Mycoplasma 74691 45.7%Bordatella 88239 54.0% Off Target 386 0.2% Total 163316 100.0% Region1/2 Reads % Identified Borrelia 36449 35.6% Bordatella 65752 64.1% OffTarget 327 0.3% Total 102528 100.0% Region 3/2 Reads % IdentifiedBartonella 22513 96.1% Borrelia 0 0.0% Bordatella 604 2.6% Off Target303 1.3% Total 23420 100.0% Region 3/2 Reads % Identified Mycoplasma 20313.7% Bordatella 1183 79.6% Off Target 100 6.7% Total 1486 100.0% Region3/2 Reads % Identified Borrelia 67 22.4% Bordatella 199 66.6% Off Target33 11.0% Total 299 100.0% Region 3/4 Reads % Identified Bartonella 24167.7% Borrelia 0 0.0% Bordatella 42 11.8% Off Target 73 20.5% Total 356100.0% Region 3/4 Reads % Identified Mycoplasma 46 8.6% Bordatella 45385.0% Off Target 34 6.4% Total 533 100.0% Region 3/4 Reads % IdentifiedBorrelia 72 14.0% Bordatella 396 77.0% Off Target 46 8.9% Total 514100.0% Region 5/4 Reads % Identified Bartonella 32806 70.8% Borrelia 680.1% Bordatella 12588 27.2% Off Target 863 1.9% Total 46325 100.0%Region 5/4 Reads % Identified Mycoplasma 49079 23.3% Bordatella 15827475.2% Off Target 3151 1.5% Total 210504 100.0% Region 5/4 Reads %Identified Borrelia 17302 40.0% Bordatella 25345 58.7% Off Target 5641.3% Total 43211 100.0%

Example 14 Pan-Bacterial Metagenomics Analysis No. 4

A blood sample from a patient was processed to extract the nucleicacids, prepare an ion amplicon library, purify the ion amplicon library,sequence the 16S rRNA in the library, and identify the species ofmicroorganisms present in the biological sample with a computer-basedgenomic analysis using the procedures described in Examples 1-8. PCRprimers were selected from those listed in Tables 4 and 5.

Sequence Information: 703297 sequence reads were obtained for DNAextracted from a blood sample. The longest 332,906 sequences wereanalyzed and compared to all available prokaryotic species.

Results Confidence Profile: At the provided quality control cut-off itis estimated that >95% of the sequence reads correctly list the genus,while >30% of the sequence reads correctly list the species.

The identified species are shown in FIG. 11.

Further examples include using the systems, methods and/or kits asdescribed herein to characterize other microorganisms, such as protozoa,viruses, and fungi. FIGS. 18-20 illustrate reports generated from amethod that detected protozoa. A PCR procedure suitable foramplification of protozoa is disclosed in application Ser. No.13/834,441, entitled SEMI-PAN-PROTOZOAL BY QUANTITATIVE PCR, filed onMar. 15, 2013, the contents of which are hereby incorporated herein byreference, to the extend such contents do not conflict with the presentdisclosure. FIG. 21 illustrates a report generated from a method thatdetected fungi. Further, by way of specific example, Adenovirus type 2was detected using a method as described herein.

Additional nonlimiting examples of the disclosure include:

1. A method of characterizing one or more microorganisms, the methodcomprising the steps of:

preparing an amplicon library with a polymerase chain reaction (PCR) ofnucleic acids;

sequencing a characteristic gene sequence in the amplicon library toobtain a gene sequence; and

characterizing the one or more microorganisms based on the gene sequenceusing a computer-based genomic analysis of the gene sequence.

2. The method of example 1, wherein the amplicon library comprises anion amplicon library.

3. The method of any of examples 1-2, further comprising a step ofextracting nucleic acids from a biological sample of a subject.

4. The method of any of examples 1-3, further comprising a step ofpurifying the amplicon library from the PCR reaction.

5. The method of any of examples 1-4, wherein the one or moremicroorganisms comprise bacteria and the characteristic gene comprises16S ribosomal RNA (16S rRNA).

6. The method of any of examples 1-5, wherein the one or moremicroorganisms comprise protozoa.

7. The method of any of examples 1-6, wherein the one or moremicroorganisms comprise fungi.

8. The method of any of examples 1-7, wherein the one or moremicroorganisms comprise viruses.

9. The method of any of examples 1-8, wherein the step of sequencingcomprises using an ion semiconductor sequencing platform or a platformbased on stepwise addition of reversible terminator nucleotides.

10. The method of any of examples 1-9, further comprising a step ofidentifying the one or more microorganisms using a computer-basedgenomic analysis of the gene sequence.

11. The method of any of examples 1-10, further comprising a step ofdetermining a nearest characterized microorganism.

12. The method of any of examples 1-11, wherein the PCR reaction uses atleast one forward primer.

13. The method of example 12, wherein the forward primer comprises atarget sequence that comprises a sequence from the characteristic gene.

14. The method of example 13, wherein the target sequence comprises asequence from a 16S rRNA gene selected from a hypervariable regionselected from the group consisting of V1, V2, V4, and V5.

15. The method of any of examples 13-14, wherein the target sequencecomprises a sequence from the 16S rRNA gene selected from the groupconsisting of (i) a sequence beginning in V1 and extending towards V2,(ii) a sequence beginning in V5 and extending towards V4, (iii) asequence beginning in V2 and extending towards V1, and (iv) a sequencebeginning in V4 and extending towards V5.

16. The method of any of examples 13-15, wherein the target sequencefrom the 16S rRNA comprises SEQ ID NO: 18 or SEQ ID NO: 19.

17. The example of any of examples 1-16, wherein the PCR reaction usesat least a first forward primer and a second forward primer, eachcomprising a barcode, a barcode adapter, and a target sequence;

wherein a target sequence of the first forward primer comprises asequence from a 16S rRNA gene beginning in V1 and extending towards V2and a target sequence of the second forward primer comprises a sequencebeginning in V5 and extending towards V4.

18. The method of any of examples 13-17, wherein the target sequencecomprises a sequence from a 16S rRNA gene selected from the groupconsisting of SEQ ID NO: 18, SEQ ID NO: 19, SEQ ID NO: 20, SEQ ID NO:21, SEQ ID NO: 22, SEQ ID NO: 23, SEQ ID NO: 24, SEQ ID NO: 25, SEQ IDNO: 26, SEQ ID NO: 27, SEQ ID NO: 28, SEQ ID NO: 29, and SEQ ID NO: 30.

19. The method of any of examples 12-18, wherein the forward primercomprises a sequence from a 16S rRNA gene selected from the groupconsisting of SEQ ID NO: 35, SEQ ID NO: 36, SEQ ID NO: 37, SEQ ID NO:38, SEQ ID NO: 39, SEQ ID NO: 40, SEQ ID NO: 41, SEQ ID NO: 42, SEQ IDNO: 43, SEQ ID NO: 44, SEQ ID NO: 45, SEQ ID NO: 46, SEQ ID NO: 47, SEQID NO: 48, SEQ ID NO: 49, and SEQ ID NO: 50.

20. The method of any of examples 1-19, wherein the PCR reaction uses areverse primer comprising SEQ ID NO: 33.

21. The method of any of examples 12-20, wherein the forward primercomprises a sequence from a 16S rRNA gene selected from the groupconsisting of SEQ ID NO: 51, SEQ ID NO: 52, SEQ ID NO: 53, SEQ ID NO:54, SEQ ID NO: 55, SEQ ID NO: 56, SEQ ID NO: 57, SEQ ID NO: 58, SEQ IDNO: 59, SEQ ID NO: 60, SEQ ID NO: 61, SEQ ID NO: 62, SEQ ID NO: 63, SEQID NO: 64, SEQ ID NO: 65, and SEQ ID NO: 66.

22. The method of any of examples 1-21, wherein the PCR reaction uses areverse primer comprising SEQ ID NO: 34.

23. The method of any of examples 3-22, wherein the biological samplecomprises material selected from a urine sample, a blood sample, a jointsample, a dental sample, a bronchioalveolar lavage, a nasal swab,cerebrospinal fluid, synovial fluid, brain tissue, cardiac tissue, bone,skin, and a lymph node tissue.

24. The method of any of examples 3-23, wherein the biological samplecomprises a dental sample and the one or more microorganisms comprises amicroorganism from a genus selected from the group consisting ofBacteroides, Tannerella, Prevotella, Peptostreptococcus, Streptococcus,Staphylococcus, Porphyromonas, Fusobacterium, Clostridium, Treponema,Atopobium, Cryptobacterium, Eubacterium, Mogibacterium, Filifactor,Dialister, Centipeda, Selenomonas, Granulicatella, and Kingella.

25. The method of any of examples 3-24, wherein the biological samplecomprises a joint sample and the one or more microorganisms comprises amicroorganism from a genus selected from the group consisting ofStaphylococcus, Streptococcus, Kingella, Aeromonas, Mycobacterium,Actinomyces, Fusobacterium, Salmonella, Haemophilus, Borrelia,Neisseria, Escherichia, Brucella, Pseudomonas, Mycoplasma, Salmonella,Propionibacterium, Acinetobacter, Treponema, and Erysipelothrix.

26. The method of any of examples 3-25, wherein the biological samplecomprises a blood sample and the one or more microorganisms comprises amicroorganism from a genus selected from the group consisting ofCapnocytophaga, Rickettsia, Staphylococcus, Streptococcus, Neisseria,Mycobacterium, Klebsiella, Haemophilus, Fusobacterium, Chlamydia,Enterococcus, Escherichia, Enterobacter, Proteus, Legionella,Pseudomonas, Clostridium, Listeria, Serratia, and Salmonella.

27. The method of any of examples 1-26, wherein the one or moremicroorganisms comprises at least one nonculturable pathogen.

28. The method of any of examples 1-27, further comprising a step ofgenerating a report with a one or more of a genera and species of theone or more microorganisms.

29. The method of example 28, wherein the report includes a relativemeasure of the one or more of genera and species contribution anddiversity in the biological sample and antimicrobial resistance andsusceptibility information for each genus and/or species.

30. The method of any of examples 1-29, further comprising treating thesubject with a treatment identified in the report.

31. The method of any of examples 1-30, wherein the computer-basedgenomic analysis comprises application of a procedural algorithm tosequencing data.

32. The method of example 31, wherein the procedural algorithm excludessequences that are present less than five times or constitute less thanone percent of the sequencing data.

33. A kit for characterizing at least one microorganism, the kitcomprising:

a) at least one forward primer comprising an adapter sequence and apriming sequence, for a target sequence, wherein the target sequencecomprises a sequence from a characteristic gene sequence; and

b) at least one reverse primer.

34. The kit of example 33, wherein the target sequence comprises asequence from a hypervariable region from a 16S rRNA gene selected fromthe group consisting of V1, V2, V4, and V5.

35. The kit of any of examples 33-34, wherein the forward primercomprises a barcode and a barcode adapter.

36. The kit of any of examples 33-35, wherein the target sequencecomprises a 16S rRNA gene sequence selected from the group consisting of(i) a sequence beginning in V1 and extending towards V2, (ii) a sequencebeginning in V5 and extending towards V4, (iii) a sequence beginning inV2 and extending towards V1, and (iv) a sequence beginning in V4 andextending towards V5.

37. The kit of any of examples 33-36, wherein the at least one forwardprimer comprises a sequence selected from the group consisting of SEQ IDNO: 18 and SEQ ID NO: 19.

38. The kit of any of examples 33-37, wherein the at least one forwardprimer comprises a first forward primer and a second forward primer,each comprising a barcode, a barcode adapter, and a target sequence;

wherein the target sequence of the first forward primer comprises asequence beginning in V1 and extending towards V2 and the targetsequence of the second forward primer comprises a sequence beginning inV5 and extending towards V4.

39. The kit of any of examples 33-38, wherein the first forward primercomprises SEQ ID NO: 18 and a second forward primer comprises SEQ ID NO:19.

40. The kit of any of examples 33-39, wherein the at least one reverseprimer comprises a sequence selected from the group consisting of SEQ IDNO: 33 and SEQ ID NO: 34.

41. The kit of any of examples 33-40, wherein the target sequence isselected from the group consisting of SEQ ID NO: 18, SEQ ID NO: 19, SEQID NO: 20, SEQ ID NO: 21, SEQ ID NO: 22, SEQ ID NO: 23, SEQ ID NO: 24,SEQ ID NO: 25, SEQ ID NO: 26, SEQ ID NO: 27, SEQ ID NO: 28, SEQ ID NO:29, and SEQ ID NO: 30.

42. The kit of any of examples 33-38, wherein the target sequence isabout 10 nucleotides in length to about 30 nucleotides in length.

43. A method of characterizing one or more microorganisms in abiological sample, the method comprising the steps of:

providing at least one forward primer comprising an adapter sequence anda primer sequence for a target sequence, wherein the target sequencecomprises a sequence from a hypervariable region from a 16S rRNA geneselected from the group consisting of V1, V2, V4, and V5;

providing at least one reverse primer;

providing a biological sample comprising nucleic acids;

preparing an amplicon library with a polymerase chain reaction (PCR) ofthe nucleic acids;

purifying the amplicon library from the PCR reaction;

sequencing a 16S ribosomal RNA (16S rRNA) gene in the ion ampliconlibrary to obtain a gene sequence; and

characterizing the one or more microorganisms based on the gene sequenceusing a computer-based genomic analysis of the 16S rRNA gene sequence.

Although any methods and materials, similar or equivalent to thosedescribed herein, can be used in the practice or testing of the presentinvention, the preferred methods and materials are described herein. Allpublications, patents, and patent publications cited are incorporated byreference herein in their entirety for all purposes, to the extent suchreferences do not conflict with the present disclosure.

It is understood that the disclosed invention is not limited to theparticular methodology, protocols and materials described as these canvary. It is also understood that the terminology used herein is for thepurposes of describing particular embodiments only and is not intendedto limit the scope of the present invention that will be limited only bythe appended claims.

Those skilled in the art will recognize, or be able to ascertain usingno more than routine experimentation, many equivalents to the specificembodiments of the invention described herein. Such equivalents areintended to be encompassed by the following claims.

What is claimed is:
 1. A method of identifying a plurality ofmicroorganisms in a biological sample comprising: a) extracting nucleicacids from the biological sample; b) preparing an ion amplicon librarywith a polymerase chain reaction (PCR) reaction of the nucleic acids; c)purifying the ion amplicon library from the PCR reaction; d) sequencinga 16S ribosomal RNA (16S rRNA) gene in the ion amplicon library with anion semiconductor sequencing platform; and e) identifying the species ofthe plurality of microorganisms with a computer-based genomic analysisof the 16S rRNA gene sequence.
 2. The method of claim 1, wherein the PCRreaction uses a forward primer comprising a barcode, a barcode adapter,and a target sequence.
 3. The method of claim 2, wherein the barcodecomprises a sequence selected from the group consisting of SEQ ID NO: 1,SEQ ID NO: 2, SEQ ID NO: 3, SEQ ID NO: 4, SEQ ID NO: 5, SEQ ID NO: 6,SEQ ID NO: 7, SEQ ID NO: 8, SEQ ID NO: 9, SEQ ID NO: 10, SEQ ID NO: 11,SEQ ID NO: 12, SEQ ID NO: 13, SEQ ID NO: 14, SEQ ID NO: 15, and SEQ IDNO:
 16. 4. The method of claim 2, wherein the barcode adaptor is SEQ IDNO:
 17. 5. The method of claim 2, wherein the target sequence comprisesa sequence from the 16S rRNA gene.
 6. The method of claim 5, wherein thesequence from the 16S rRNA is selected from the group consisting of SEQID NO: 18, SEQ ID NO: 19, SEQ ID NO: 20, SEQ ID NO: 21, SEQ ID NO: 22,SEQ ID NO: 23, SEQ ID NO: 24, SEQ ID NO: 25, SEQ ID NO: 26, SEQ ID NO:27, SEQ ID NO: 28, SEQ ID NO: 29, and SEQ ID NO:
 30. 7. The method ofclaim 6, wherein the target sequence comprises SEQ ID NO:
 18. 8. Themethod of claim 6, wherein the target sequence comprises SEQ ID NO: 19.9. The method of claim 2, wherein the forward primer comprises asequence selected from the group consisting of SEQ ID NO: 35, SEQ ID NO:36, SEQ ID NO: 37, SEQ ID NO: 38, SEQ ID NO: 39, SEQ ID NO: 40, SEQ IDNO: 41, SEQ ID NO: 42, SEQ ID NO: 43, SEQ ID NO: 44, SEQ ID NO: 45, SEQID NO: 46, SEQ ID NO: 47, SEQ ID NO: 48, SEQ ID NO: 49, and SEQ ID NO:50.
 10. The method of claim 9, wherein the PCR reaction uses a reverseprimer comprising SEQ ID NO:
 33. 11. The method of claim 2, wherein theforward primer comprises a sequence selected from the group consistingof SEQ ID NO: 51, SEQ ID NO: 52, SEQ ID NO: 53, SEQ ID NO: 54, SEQ IDNO: 55, SEQ ID NO: 56, SEQ ID NO: 57, SEQ ID NO: 58, SEQ ID NO: 59, SEQID NO: 60, SEQ ID NO: 61, SEQ ID NO: 62, SEQ ID NO: 63, SEQ ID NO: 64,SEQ ID NO: 65, and SEQ ID NO:
 66. 12. The method of claim 11, whereinthe PCR reaction uses a reverse primer comprising SEQ ID NO:
 34. 13. Themethod of claim 1, wherein the biological sample is selected from aurine sample, a blood sample, a bronchioalveolar lavage, a nasal swab,cerebrospinal fluid, synovial fluid, brain tissue, cardiac tissue, bone,skin, a lymph node tissue, and a dental tissue.
 14. The method of claim13, wherein the dental tissue is a tooth, a soft tissue, or dental pulp.15. The method of claim 1, wherein the plurality of microorganismscomprises a bacterial pathogen.
 16. The method of claim 1, wherein theplurality of microorganisms comprises a nonculturable pathogen.
 17. Themethod of claim 1, wherein the plurality of microorganisms comprises apathogenic community of microorganisms.
 18. The method of claim 1,further comprising generating a report with the species of the pluralityof microorganisms.
 19. The method of claim 18, wherein the reportincludes antibiotic resistance information for each species.
 20. Themethod of claim 1, wherein the computer-based genomic analysis comprisesapplication of a procedural algorithm to sequencing data.